WO2019154208A1

WO2019154208A1 - Systems and methods for determining operation strategy for service platform

Info

Publication number: WO2019154208A1
Application number: PCT/CN2019/073855
Authority: WO
Inventors: Lingyu Zhang
Original assignee: Beijing Didi Infinity Technology And Development Co., Ltd.
Priority date: 2018-02-06
Filing date: 2019-01-30
Publication date: 2019-08-15
Also published as: CN110309399A

Abstract

A method for determining a day type of a target date among a plurality of day types are provided. The method may include obtaining overall operation data of a service platform associated with the target date. For each of the day types, the method may also include obtaining overall historical operation data of the service platform associated with one or more first historical dates, and determining a difference between the overall operation data and the corresponding overall historical operation data using a loss function, wherein the first historical date (s) are of the day type and associated with the target date. The method may further include determining the day type of the target date based on the differences corresponding to the day types, and determining an operation strategy with respect to a registered user terminal of the service system based on the day type of the target date.

Description

SYSTEMS AND METHODS FOR DETERMINING OPERATION STRATEGY FOR SERVICE PLATFORM

CROSS-REFERENCE TO RELATED APPLICATION

This application claims priority of Chinese Patent Application No. 201810118470.6, filed on February 6, 2018, the contents of which are hereby incorporated by reference.

TECHNICAL FIELD

The present disclosure generally relates to service platforms, and in particular, to systems and methods for determining an operation strategy for an online service platform based on a day type of a target date.

BACKGROUND

With the development of Internet technology online services, such as online to offline (O2O) services, play a more and more significant role in people’s daily lives. Normally, service requesters of an online service platform have different service demands on different types of days (e.g., a working day, a rest day, a weekend, a holiday) . For example, passengers of an online transportation service platform usually hail vehicles to their workplaces on workdays and to other places on weekends. On the other hand, service providers of the online service platform may need to meet different service demands on different types of days. It is necessary for the online service platform to adopt different operation strategies with respect to the service requesters and/or the service providers on different types of days, so as to better meet the service demands of service requesters and/or to improve the service efficiency of the service providers. Generally, a day type of a target date can be determined by looking up a calendar. However, the calendar may not necessarily have precise day types of some particular target dates. For example, a Monday, which is supposed to be a workday, may actually be a rest day because of a specific festival. In addition, more and more day types, such as folk festivals, have appeared, which are probably not recorded in the calendar. Thus, it is desirable to provide systems and methods for determining a day type of a target date efficiently and determining an operation strategy for the service platform to adopt on the target date according to the day type of the target date.

SUMMARY

According to one aspect of the present disclosure, a system for determining a day type of a target date among a plurality of day types is provided. The system may include a communication port communicatively connected to a network, at least one storage medium including a set of instructions, and at least one processor in communication with the communication port and the at least one storage medium. When executing the instructions, the at least one processor may be configured to direct the system to perform the following operations. The at least one processor may obtain overall operation data of a service platform associated with the target date. The service platform may be configured to communicate with at least one user terminal via the communication port. For each of the plurality of day types, the at least one processor may obtain overall historical operation data of the service platform associated with one or more first historical dates, wherein the one or more first historical dates may be of the day type and associated with the target date. For each of the plurality of day types, the at least one processor may also determine a difference between the overall operation data and the corresponding overall historical operation data using a loss function. An input to the loss function may include the overall operation data and the corresponding overall historical operation data. The at least one processor may also determine the day type of the target date based on the differences corresponding to the plurality of day types. The at least one processor may also determine an operation strategy with respect to the registered user terminal of the service platform based on the day type of the target date.

In some embodiments, the overall operation data may include a plurality of sets of operation data of the service platform in a plurality of time periods during the target date. Each of the plurality of sets of operation data may correspond to one of the plurality of time periods. For each of the plurality of day types, the corresponding overall historical operation data may include a plurality of sets of historical operation data of the service platform in the plurality of time periods during the one or more first historical dates. Each of the plurality of sets of historical operation data may correspond to one of the plurality of time periods.

In some embodiments, the loss function may include a first component and a second component. For each of the plurality of day types, the first component may be configured to determine, for each of plurality of time periods, a first difference between a set of operation data of the time period and the corresponding set of historical operation data of the time period. The second component may be configured to determine the difference between the overall operation data and the corresponding overall historical operation data based on the first differences corresponding to the plurality of time periods.

In some embodiments, for each of the plurality of day types, to determine a difference between the overall operation data and the corresponding overall historical operation data using a loss function, the at least one processor may obtain one or more day types of one or more second historical dates associated with the target date. The at least one processor may also determine an initial day type of the target date based on the one or more day types of the one or more second historical dates. For the day type, the at least one processor may also determine the difference between the overall operation data and the corresponding overall historical operation data using the loss function. An input to the loss function may include the overall operation data, the corresponding overall historical operation data, and the initial day type of the target date.

In some embodiments, the loss function may include a third component and a fourth component. For each of the plurality of day types, the third component may be configured to determine an initial difference between the overall operation data and the corresponding overall historical operation data. The fourth component may be configured to determine the difference between the overall operation data and the corresponding overall historical operation data based on the initial difference and the initial day type of the target date.

In some embodiments, the at least one processor may also obtain temporal information of the target date. The at least one processor may also obtain temporal information and day types of a plurality of third historical dates. For each of the plurality of day types, the at least one processor may further determine the one or more first historical dates being of the day type and associated with the target date among the plurality of third historical dates based on the temporal information of the target date, the temporal information of the plurality of third historical dates, and the day types of the plurality of third historical dates.

In some embodiments, the at least one processor may also determine that the target date is a rest day. In response to a determination that the target date is a rest day, the at least one processor may also obtain temporal information of the target date, and determine whether the target date relates to a festival based on the temporal information of the target date.

In some embodiments, the loss function may be at least one of a linear loss function, an absolute loss function, a quadratic loss function, or a square root loss function.

In some embodiments, the day type of the target date may be at least one of a working day, a rest day, a weekend, a holiday, or a festival.

In some embodiments, to determine an operation strategy with respect to the registered user terminal of the service platform based on the day type of the target date, the at least one processor may also obtain preference information relating to a user of the at least one registered user terminal according to the day type of the target date. The at least one processor may also determine a message for presentation on the at least one registered user terminal based on the preference information relating to the user.

In some embodiments, to determine an operation strategy with respect to the registered user terminal of the service platform based on the day type of the target date, the at least one processor may also determine a strategy for dispatching a user of the at least one registered user terminal on the target date based on the day type of the target date.

In some embodiments, the loss function may be determined according to a loss function determination process. The loss function determination process may include obtaining overall sample operation data associated with a sample target date and a day type of the sample target date. For each of the plurality of day types, the loss function determination process may also include obtaining overall sample historical operation data associated with one or more sample historical dates. The one or more sample historical dates may be of the day type and associated with the sample target date. The loss function determination process may also include obtaining a plurality of candidate loss functions. The loss function determination process may further include selecting, from the plurality of candidate loss functions, the loss function based at least in part on the overall sample operation data, the day type of the sample target date, and the overall sample historical operation data corresponding to the plurality of day types.

According to another aspect of the present disclosure, a method for determining a day type of a target date among a plurality of day types is provided. The method may include obtaining overall operation data of a service platform associated with the target date. The service platform may be configured to communicate with at least one user terminal. For each of the plurality of day types, the method may also include obtaining overall historical operation data of the service platform associated with one or more first historical dates, wherein the one or more first historical dates may be of the day type and associated with the target date. For each of the plurality of day types, the method may also include determining a difference between the overall operation data and the corresponding overall historical operation data using a loss function. An input to the loss function may include the overall operation data and the corresponding overall historical operation data. The method may also include determining the day type of the target date based on the differences corresponding to the plurality of day types. The method may also include determining an operation strategy with respect to the registered user terminal of the service platform based on the day type of the target date.

According to another aspect of the present disclosure, a system for determining a day type of a target date among a plurality of day types is provided. The system may include an obtaining module and a determination module. The obtaining module may be configured to obtain overall operation data of a service platform associated with the target date. The service platform may be configured to communicate with at least one user terminal via a communication port. For each of the plurality of day types, the obtaining module may be configured to obtain overall historical operation data of the service platform associated with one or more first historical dates, wherein the one or more first historical dates may be of the day type and associated with the target date. For each of the plurality of day types, the determination module may be configured to determine a difference between the overall operation data and the corresponding overall historical operation data using a loss function. An input to the loss function may include the overall operation data and the corresponding overall historical operation data. The determination module may also be configured to determine the day type of the target date based on the differences corresponding to the plurality of day types. The determination module may also be configured to determine an operation strategy with respect to the registered user terminal of the service platform based on the day type of the target date.

According to still another aspect of the present disclosure, a non-transitory computer-readable storage medium embodying a computer program product is provided. The computer program product comprising instructions may be configured to cause a computing device to perform one or more of the following operations. The computing device may obtain overall operation data of a service platform associated with the target date. The service platform may be configured to communicate with at least one user terminal via a communication port. For each of the plurality of day types, the computing device may obtain overall historical operation data of the service platform associated with one or more first historical dates, wherein the one or more first historical dates may be of the day type and associated with the target date. For each of the plurality of day types, the computing device may also determine a difference between the overall operation data and the corresponding overall historical operation data using a loss function. An input to the loss function may include the overall operation data and the corresponding overall historical operation data. The computing device may also determine the day type of the target date based on the differences corresponding to the plurality of day types. The computing device may also determine an operation strategy with respect to the registered user terminal of the service platform based on the day type of the target date.

According to another aspect of the present disclosure, a system for a determining a loss function used in identifying a day type of a date is provided. The system may include at least one storage medium including a set of instructions, and at least one processor in communication with the at least one storage medium. When executing the instructions, the at least one processor may be configured to direct the system to perform the following operations. The at least one processor may obtain a day type of a sample target date and overall sample operation data of a service platform associated with the sample target date. For each of a plurality of day types, the at least one processor may also obtain overall sample historical operation data of the service platform associated with one or more first sample historical dates, wherein the one or more first sample historical dates may be of the day type and associated with the sample target date. The at least one processor may also obtain a plurality of candidate loss functions. The at least one processor may also select the loss function from the plurality of candidate loss functions based at least in part on the overall sample operation data, the day type of the sample target date, and the overall sample historical operation data corresponding to the plurality of day types.

In some embodiments, to select the loss function from the plurality of candidate loss functions, the at least one processor may determine, for each of the plurality of candidate loss functions, a predicted day type of the sample target date using the candidate loss function based on the overall sample operation data and the overall sample historical operation data. For each of the plurality of candidate loss functions, the at least one processor may also determine an accuracy score of the candidate loss function based at least in part on the predicted day type and the day type of the sample target date. The at least one processor may also designate the candidate loss function having the highest accuracy score among the plurality of candidate loss functions as the loss function.

In some embodiments, for each of the plurality of candidate loss functions, to determine a predicted day type of the sample target date using the candidate loss function, the at least one processor may determine, for each of the plurality of day types, a sample difference between the overall sample operation data and the corresponding overall sample historical operation data using the candidate loss function. An input to the candidate loss function may include the overall sample operation data and the corresponding overall sample historical operation data. The at least one processor may also determine the predicted day type of the sample target date based on the sample differences corresponding to the plurality of day types.

In some embodiments, the overall sample operation data may include a plurality of sets of sample operation data in a plurality of time periods during the sample target date, each of the plurality of sets of sample operation data corresponding to one of the plurality of time periods. For each of the plurality of day types, the corresponding overall sample historical operation data may include a plurality of sets of sample historical operation data in the plurality of time periods during the corresponding one or more first sample historical dates. Each of the plurality of sets of sample historical operation data may correspond to one of the plurality of time periods.

In some embodiments, at least one candidate loss function may include a first component and a second component. For each of the plurality of day types, the first component may be configured to determine, for each of plurality of time periods, a first sample difference between the set of sample operation data in the time period and the corresponding set of sample historical operation data in the time period. The second component may be configured to determine the sample difference between the overall sample operation data and the corresponding overall sample historical operation data based on the first sample differences corresponding to the plurality of time periods.

In some embodiments, for each of the plurality of day types, to determine a sample difference between the overall sample operation data and the corresponding overall sample historical operation data using the candidate loss function, the at least one processor may obtain one or more day types of one or more second sample historical dates associated with the sample target date. The at least one processor may also determine an initial day type of the sample target date based on the one or more day types of the one or more second sample historical dates. For the day type, the at least one processor may also determine the sample difference between the overall sample operation data and the corresponding overall sample historical operation data using the candidate loss function. An input of the candidate loss function may include the overall sample operation data, the corresponding overall sample historical operation data, and the initial day type of the sample target date.

According to another aspect of the present disclosure, a method for a determining a loss function used in identifying a day type of a date is provided. The method may include obtaining a day type of a sample target date and overall sample operation data of a service platform associated with the sample target date. For each of a plurality of day types, the method may also include obtaining overall sample historical operation data of the service platform associated with one or more first sample historical dates, wherein the one or more first sample historical dates may be of the day type and associated with the sample target date. The method may also include obtaining a plurality of candidate loss functions. The method may also include selecting the loss function from the plurality of candidate loss functions based at least in part on the overall sample operation data, the day type of the sample target date, and the overall sample historical operation data corresponding to the plurality of day types.

According to another aspect of the present disclosure, a system for a determining a loss function used in identifying a day type of a date is provided. The system may include an obtaining module and a selection module. The obtaining module may be configured to obtain a day type of a sample target date and overall sample operation data of a service platform associated with the sample target date. For each of a plurality of day types, the obtaining module may also be configured to obtain overall sample historical operation data of the service platform associated with one or more first sample historical dates, wherein the one or more first sample historical dates may be of the day type and associated with the sample target date. The obtaining module may also be configured to obtain a plurality of candidate loss functions. The selection module may be configured to select the loss function from the plurality of candidate loss functions based at least in part on the overall sample operation data, the day type of the sample target date, and the overall sample historical operation data corresponding to the plurality of day types.

According to another aspect of the present disclosure, a non-transitory computer-readable storage medium embodying a computer program product is provided. The computer program product comprising instructions may be configured to cause a computing device to performing the following operations. The computing device may obtain a day type of a sample target date and overall sample operation data of a service platform associated with the sample target date. For each of a plurality of day types, the computing device may also obtain overall sample historical operation data of the service platform associated with one or more first sample historical dates, wherein the one or more first sample historical dates may be of the day type and associated with the sample target date. The computing device may also obtain a plurality of candidate loss functions. The computing device may also select the loss function from the plurality of candidate loss functions based at least in part on the overall sample operation data, the day type of the sample target date, and the overall sample historical operation data corresponding to the plurality of day types.

Additional features will be set forth in part in the description which follows, and in part will become apparent to those skilled in the art upon examination of the following and the accompanying drawings or may be learned by production or operation of the examples. The features of the present disclosure may be realized and attained by practice or use of various aspects of the methodologies, instrumentalities and combinations set forth in the detailed examples discussed below.

BRIEF DESCRIPTION OF THE DRAWINGS

The present disclosure is further described in terms of exemplary embodiments. These exemplary embodiments are described in detail with reference to the drawings. These embodiments are non-limiting exemplary embodiments, in which like reference numerals represent similar structures throughout the several views of the drawings, and wherein:

FIG. 1 is a schematic diagram illustrating an exemplary service system according to some embodiments of the present disclosure;

FIG. 2 is a schematic diagram illustrating exemplary hardware and/or software components of a computing device according to some embodiments of the present disclosure;

FIG. 3 is a schematic diagram illustrating exemplary hardware and/or software components of a mobile device according to some embodiments of the present disclosure;

FIG. 4A and FIG. 4B are block diagrams illustrating exemplary processing devices according to some embodiments of the present disclosure;

FIG. 5 is a flowchart illustrating an exemplary process for determining an operation strategy with respect to a registered user terminal of a service platform according to some embodiments of the present disclosure;

FIG. 6 is a flowchart illustrating an exemplary process for determining a loss function used in identifying a day type of a date according to some embodiments of the present disclosure;

FIG. 7 is a flowchart illustrating an exemplary process for selecting a loss function among a plurality of candidate loss functions according to some embodiments of the present disclosure;

FIG. 8 is a block diagram illustrating exemplary processing device according to some embodiments of the present disclosure; and

FIG. 9 is a flowchart illustrating an exemplary process for recommending information to a user based on a day type of a target date according to some embodiments of the present disclosure.

DETAILED DESCRIPTION

The following description is presented to enable any person skilled in the art to make and use the present disclosure, and is provided in the context of a particular application and its requirements. Various modifications to the disclosed embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other embodiments and applications without departing from the spirit and scope of the present disclosure. Thus, the present disclosure is not limited to the embodiments shown, but is to be accorded the widest scope consistent with the claims.

The terminology used herein is to describe particular example embodiments only and is not intended to be limiting. As used herein, the singular forms "a, " "an, " and "the" may be intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprise, " "comprises, " and/or "comprising, " "include, " "includes, " and/or "including, " when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

These and other features, and characteristics of the present disclosure, as well as the methods of operation and functions of the related elements of structure and the combination of parts and economies of manufacture, may become more apparent upon consideration of the following description with reference to the accompanying drawings, all of which form a part of this disclosure. It is to be expressly understood, however, that the drawings are for the purpose of illustration and description only and are not intended to limit the scope of the present disclosure. It is understood that the drawings are not to scale.

The flowcharts used in the present disclosure illustrate operations that systems implement according to some embodiments in the present disclosure. It is to be expressly understood, the operations of the flowchart may be implemented not in order. Conversely, the operations may be implemented in inverted order, or simultaneously. Moreover, one or more other operations may be added to the flowcharts. One or more operations may be removed from the flowcharts.

Moreover, while the system and method in the present disclosure is described primarily in regard to distributing a request for a transportation service, it should also be understood that the present disclosure is not intended to be limiting. The system or method of the present disclosure may be applied to any other kind of services. For example, the system or method of the present disclosure may be applied to transportation systems of different environments including land, ocean, aerospace, or the like, or any combination thereof. The vehicle of the transportation systems may include a taxi, a private car, a hitch, a bus, a train, a bullet train, a high speed rail, a subway, a vessel, an aircraft, a spaceship, a hot-air balloon, a driverless vehicle, or the like, or any combination thereof. The transportation system may also include any transportation system for management and/or distribution, for example, a system for sending and/or receiving an express. The application of the system or method of the present disclosure may be implemented on a user device and include a webpage, a plug-in of a browser, a client terminal, a custom system, an internal analysis system, an artificial intelligence robot, or the like, or any combination thereof.

The term "passenger, " "requester, " "service requester, " and "customer" in the present disclosure are used interchangeably to refer to an individual, an entity, or a tool that may request or order a service. Also, the term "driver, " "provider, " and "service provider" in the present disclosure are used interchangeably to refer to an individual, an entity, or a tool that may provide a service or facilitate the providing of the service.

The term "service request, " "request for a service, " "requests, " and "order" in the present disclosure are used interchangeably to refer to a request that may be initiated by a passenger, a service requester, a customer, a driver, a provider, a service provider, or the like, or any combination thereof. The service request may be accepted by any one of a passenger, a service requester, a customer, a driver, a provider, or a service provider. The service request may be chargeable or free.

The term "service provider terminal, ” “provider terminal, ” and "driver terminal" in the present disclosure are used interchangeably to refer to a mobile terminal that is used by a service provider to provide a service or facilitate the providing of the service. The term "service requester terminal, " “requester terminal, ” and "passenger terminal" in the present disclosure are used interchangeably to refer to a mobile terminal that is used by a service requester to request or order a service.

The positioning technology used in the present disclosure may be based on a global positioning system (GPS) , a global navigation satellite system (GLONASS) , a compass navigation system (COMPASS) , a Galileo positioning system, a quasi-zenith satellite system (QZSS) , a wireless fidelity (WiFi) positioning technology, or the like, or any combination thereof. One or more of the above positioning systems may be used interchangeably in the present disclosure.

An aspect of the present disclosure relates to systems and methods for determining a day type of a target date, wherein the day type of the target date may be used in determining an operation strategy for a service platform to adopt on the target date. The day type of the target date may be determined from a plurality of day types, such as a working day, a rest day, a weekend, a holiday, a festival, or the like, or any combination thereof. The systems and methods may obtain overall operation data of a service platform associated with the target date (e.g., a count of completed service orders per hour during a particular period in the target date) . For each of the day types, the systems and methods may determine one or more historical dates being of the day type and associated with the target date. For each of the day types, the systems and the methods may obtain overall historical operation data of the service platform associated with the corresponding historical date (s) . For each of the day types, the systems and methods may determine a difference between the overall operation data and the corresponding overall historical operation data using a loss function. According to the differences corresponding to the day types, the systems and methods may determine the day type of the target date. For example, the day type having the smallest difference among the day types may be designated as the day type of the target date. The systems and methods may further determine an operation strategy with respect to one or more registered user terminals of the service platform based on the day type of the target date.

In some embodiments of the present disclosure, the day type of the target date may be determined using the loss function based on the overall operation data of the service platform in the target date and the overall historical operation data of in the service platform in the first historical dates of different day types. Compared with a determination of the day type of the target date by looking up a calendar, the systems and methods disclosed in the present disclosure may allow use of information of multiple dimensions to automatically determine the day type of the target date. Information of multiple dimensions may include information from, e.g., different times (e.g., historical information, real time information) , different sources (information from different users including service requesters, service providers, etc. ) to improve reliability or accuracy of the determination. Moreover, the automatic determination of the day type of the target day may further facilitate automatic determination of an operation strategy for the target day. One of the problems solved by the systems and methods of the present disclosure is the big data problem and its real time application faced by an online service platform including, for example, an ineffective use of data for determining a day type of a date and an operation strategy of the online service platform for different day types. These problems raise in the online service platform appeared in the post-Internet era, and the present disclosure provides solutions to these problems in a technical manner.

FIG. 1 is a schematic diagram illustrating an exemplary service system according to some embodiments of the present disclosure. Service system 100 may be configured to provide one or more services. The service (s) may include any product, such as but not limited to food, medicine, commodity, chemical product, electrical appliance, clothing, car, housing, luxury, a servicing product, a financial product, a knowledge product, and an Internet product. In some embodiments, the service (s) may include an O2O service. Exemplary O2O services may include a transportation service (e.g., a taxi-hailing service, a chauffeur service, an express car service, a carpool service, a bus service, a driver hire service, and a shuttle service) , a meal booking service, a delivery service, a meal service, a shopping service, or the like, or any combination thereof. For example, the service system 100 may be an online transportation service platform for transportation services, an online delivery service platform for meal delivery services, an online shopping service platform for shopping services, etc.

For illustration purposes, the following description regarding the service system 100 is provided with reference to an online transportation service system. As illustrated in FIG. 1, the service system 100 may include a server 110, a network 120, a requester terminal 130, a provider terminal 140, a vehicle 150, a storage device 160, and a navigation system 170. In some embodiments, the server 110 may be a single server or a server group. The server group may be centralized or distributed (e.g., the server 110 may be a distributed system) . In some embodiments, the server 110 may be local or remote. For example, the server 110 may access information and/or data stored in the requester terminal 130, the provider terminal 140, and/or the storage device 160 via the network 120. As another example, the server 110 may be directly connected to the requester terminal 130, the provider terminal 140, and/or the storage device 160 to access stored information and/or data. In some embodiments, the server 110 may be implemented on a cloud platform. Merely by way of example, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an inter-cloud, a multi-cloud, or the like, or any combination thereof. In some embodiments, the server 110 may be implemented on a computing device 200 having one or more components illustrated in FIG. 2 in the present disclosure.

In some embodiments, the server 110 may include a processing device 112. According to some embodiments of the present disclosure, the processing device 112 may process information and/or data related to a target date to perform one or more functions described in the present disclosure. For example, the processing device 112 may process operation data of the service system 100 associated with the target date to determine a day type of the target date. The processing device 112 may further determine an operation strategy with respect to one or more registered user terminals of the service system 100 (e.g., one or more requester terminals 130 and/or one or more provider terminals 140) according to the day type of the target date. As another example, the processing device 112 may determine a loss function for identifying a day type of the target date based on sample data.

In some embodiments, the processing device 112 may include one or more processing devices (e.g., single-core processing device (s) or multi-core processor (s) ) . Merely by way of example, the processing device 112 may include a central processing unit (CPU) , an application-specific integrated circuit (ASIC) , an application-specific instruction-set processor (ASIP) , a graphics processing unit (GPU) , a physics processing unit (PPU) , a digital signal processor (DSP) , a field-programmable gate array (FPGA) , a programmable logic device (PLD) , a controller, a microcontroller unit, a reduced instruction-set computer (RISC) , a microprocessor, or the like, or any combination thereof.

The network 120 may facilitate exchange of information and/or data. In some embodiments, one or more components of the service system 100 (e.g., the server 110, the requester terminal 130, the provider terminal 140, the vehicle 150, the storage device 160, or the navigation system 170) may transmit information and/or data to other component (s) of the service system 100 via the network 120. For example, the server 110 may obtain operation data or historical operation data of the service system 100 from a storage device (e.g., the storage device 160) via the network 120. In some embodiments, the network 120 may be any type of wired or wireless network, or combination thereof. Merely by way of example, the network 120 may include a cable network, a wireline network, an optical fiber network, a telecommunications network, an intranet, an Internet, a local area network (LAN) , a wide area network (WAN) , a wireless local area network (WLAN) , a metropolitan area network (MAN) , a public telephone switched network (PSTN) , a Bluetooth network, a ZigBee network, a near field communication (NFC) network, or the like, or any combination thereof. In some embodiments, the network 120 may include one or more network access points. For example, the network 120 may include wired or wireless network access points such as base stations and/or internet exchange points 120-1, 120-2, through which one or more components of the service system 100 may be connected to the network 120 to exchange data and/or information.

In some embodiments, a service requester may be an owner of the requester terminal 130. In some embodiments, the owner of the requester terminal 130 may be someone other than the service requester. For example, an owner A of the requester terminal 130 may use the requester terminal 130 to transmit a service request for a service requester B or receive a service confirmation and/or information or instructions from the server 110. In some embodiments, a service provider may be a user of the provider terminal 140. In some embodiments, the user of the provider terminal 140 may be someone other than the service provider. For example, a user C of the provider terminal 140 may use the provider terminal 140 to receive a service request for a service provider D, and/or information or instructions from the server 110. In some embodiments, “requester, ” "service requester" and "requester terminal" may be used interchangeably, and “provider, ” "service provider, " and "service provider terminal" may be used interchangeably. In some embodiments, the service provider terminal may be associated with one or more service providers (e.g., a night-shift service provider, or a day-shift service provider) .

In some embodiments, the requester terminal 130 may include a mobile device 130-1, a tablet computer 130-2, a laptop computer 130-3, a built-in device in a vehicle 130-4, a wearable device 130-5, or the like, or any combination thereof. In some embodiments, the mobile device 130-1 may include a smart home device, a smart mobile device, a virtual reality device, an augmented reality device, or the like, or any combination thereof. In some embodiments, the smart home device may include a smart lighting device, a control device of an intelligent electrical apparatus, a smart monitoring device, a smart television, a smart video camera, an interphone, or the like, or any combination thereof. In some embodiments, the smart mobile device may include a smartphone, a personal digital assistant (PDA) , a gaming device, a navigation device, a point of sale (POS) device, or the like, or any combination thereof. In some embodiments, the virtual reality device and/or the augmented reality device may include a virtual reality helmet, virtual reality glasses, a virtual reality patch, an augmented reality helmet, augmented reality glasses, an augmented reality patch, or the like, or any combination thereof. For example, the virtual reality device and/or the augmented reality device may include Google ^TM Glasses, an Oculus Rift ^TM, a HoloLens ^TM, a Gear VR ^TM, etc. In some embodiments, the built-in device in the vehicle 130-4 may include an onboard computer, an onboard television, etc. In some embodiments, the wearable device 130-5 may include a smart bracelet, a smart footgear, smart glasses, a smart helmet, a smart watch, smart clothing, a smart backpack, a smart accessory, or the like, or any combination thereof. In some embodiments, the requester terminal 130 may be a device with positioning technology for locating the position of the service requester and/or the requester terminal 130.

The provider terminal 140 may include a plurality of provider terminals 140-1, 140-2, …, 140-n. In some embodiments, the provider terminal 140 may be similar to, or the same device as the requester terminal 130. In some embodiments, the provider terminal 140 may be customized to be able to implement the service system 100. In some embodiments, the provider terminal 140 may be a device with positioning technology for locating the service provider, the provider terminal 140, and/or the vehicle 150 associated with the provider terminal 140. In some embodiments, the requester terminal 130 and/or the provider terminal 140 may communicate with another positioning device to determine the position of the service requester, the requester terminal 130, the service provider, and/or the provider terminal 140. In some embodiments, the requester terminal 130 and/or the provider terminal 140 may periodically transmit the positioning information to the server 110. In some embodiments, the provider terminal 140 may also periodically transmit the availability status to the server 110. The availability status may indicate whether the vehicle 150 associated with the provider terminal 140 is available to carry a service requester. For example, the requester terminal 130 and/or the provider terminal 140 may transmit the positioning information and the availability status to the server 110 every thirty minutes. As another example, the requester terminal 130 and/or the provider terminal 140 may transmit the positioning information and the availability status to the server 110 each time the user logs into the mobile application associated with the service system 100.

In some embodiments, the provider terminal 140 may correspond to one or more vehicles 150. The vehicles 150 may carry the service requester and travel to a destination requested by the service requester. The vehicles 150 may include a plurality of vehicles 150-1, 150-2, …, 150-n. One vehicle may correspond to one type of services (e.g., a taxi-hailing service, a chauffeur service, an express car service, a carpool service, a bus service, a driver hire service, or a shuttle service) .

The storage device 160 may store data and/or instructions. In some embodiments, the storage device 160 may store data obtained from the requester terminal 130 and/or the provider terminal 140. In some embodiments, the storage device 160 may store data and/or instructions that the server 110 may execute or use to perform exemplary methods described in the present disclosure. For example, the storage device 160 may store operation data and/or historical operation data of the service system 100. As another example, the storage device 160 may store a day type of a plurality of dates. In some embodiments, the storage device 160 may include a mass storage device, a removable storage device, a volatile read-and-write memory, a read-only memory (ROM) , or the like, or any combination thereof. Exemplary mass storage may include a magnetic disk, an optical disk, a solid-state drive, etc. Exemplary removable storage may include a flash drive, a floppy disk, an optical disk, a memory card, a zip disk, a magnetic tape, etc. Exemplary volatile read-and-write memory may include a random-access memory (RAM) . Exemplary RAM may include a dynamic RAM (DRAM) , a double date rate synchronous dynamic RAM (DDR SDRAM) , a static RAM (SRAM) , a thyristor RAM (T-RAM) , and a zero-capacitor RAM (Z-RAM) , etc. Exemplary ROM may include a mask ROM (MROM) , a programmable ROM (PROM) , an erasable programmable ROM (EPROM) , an electrically-erasable programmable ROM (EEPROM) , a compact disk ROM (CD-ROM) , and a digital versatile disk ROM, etc. In some embodiments, the storage device 160 may be implemented on a cloud platform. Merely by way of example, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an inter-cloud, a multi-cloud, or the like, or any combination thereof.

In some embodiments, the storage device 160 may be connected to the network 120 to communicate with one or more components of the service system 100 (e.g., the server 110, the requester terminal 130, or the provider terminal 140) . One or more components of the service system 100 may access the data or instructions stored in the storage device 160 via the network 120. In some embodiments, the storage device 160 may be directly connected to or communicate with one or more components of the service system 100 (e.g., the server 110, the requester terminal 130, the provider terminal 140) . In some embodiments, the storage device 160 may be part of the server 110.

The navigation system 170 may determine information associated with an object, for example, one or more of the requester terminal 130, the provider terminal 140, the vehicle 150, etc. In some embodiments, the navigation system 170 may be a global positioning system (GPS) , a global navigation satellite system (GLONASS) , a compass navigation system (COMPASS) , a BeiDou navigation satellite system, a Galileo positioning system, a quasi-zenith satellite system (QZSS) , etc. The information may include a location, an elevation, a velocity, or an acceleration of the object, or a current time. The navigation system 170 may include one or more satellites, for example, a satellite 170-1, a satellite 170-2, and a satellite 170-3. The satellites 170-1 through 170-3 may determine the information mentioned above independently or jointly. The navigation system 170 may transmit the information mentioned above to the network 120, the requester terminal 130, the provider terminal 140, or the vehicle 150 via wireless connections.

In some embodiments, one or more components of the service system 100 (e.g., the server 110, the requester terminal 130, the provider terminal 140) may have permissions to access the storage device 160. In some embodiments, one or more components of the service system 100 may read and/or modify information related to the service requester, the service provider, and/or the public when one or more conditions are met. For example, the server 110 may read and/or modify one or more service requesters’ information after a service is completed. As another example, the server 110 may read and/or modify one or more service providers’ information after a service is completed.

In some embodiments, information exchanging of one or more components of the service system 100 may be initiated by way of requesting a service. The object of the service request may be any product. In some embodiments, the product may include food, medicine, commodity, chemical product, electrical appliance, clothing, car, housing, luxury, or the like, or any combination thereof. In some other embodiments, the product may include a servicing product, a financial product, a knowledge product, an Internet product, or the like, or any combination thereof. The Internet product may include an individual host product, a web product, a mobile Internet product, a commercial host product, an embedded product, or the like, or any combination thereof. The mobile internet product may be used in a software of a mobile terminal, a program, a system, or the like, or any combination thereof. The mobile terminal may include a tablet computer, a laptop computer, a mobile phone, a personal digital assistant (PDA) , a smart watch, a point of sale (POS) device, an onboard computer, an onboard television, a wearable device, or the like, or any combination thereof. For example, the product may be any software and/or application used on the computer or mobile phone. The software and/or application may relate to socializing, shopping, transporting, entertainment, learning, investment, or the like, or any combination thereof. In some embodiments, the software and/or application related to transporting may include a traveling software and/or application, a vehicle scheduling software and/or application, a mapping software and/or application, etc. In the vehicle scheduling software and/or application, the vehicle may include a horse, a carriage, a rickshaw (e.g., a wheelbarrow, a bike, a tricycle, etc. ) , a car (e.g., a taxi, a bus, a private car, etc. ) , a train, a subway, a vessel, an aircraft (e.g., an airplane, a helicopter, a space shuttle, a rocket, a hot-air balloon, etc. ) , or the like, or any combination thereof.

One of ordinary skill in the art would understand that when an element (or component) of the service system 100 performs, the element may perform through electrical signals and/or electromagnetic signals. For example, when a requester terminal 130 transmits out a service request to the server 110, a processor of the requester terminal 130 may generate an electrical signal encoding the service request. The processor of the requester terminal 130 may then transmit the electrical signal to an output port. If the requester terminal 130 communicates with the server 110 via a wired network, the output port may be physically connected to a cable, which further may transmit the electrical signal to an input port of the server 110. If the requester terminal 130 communicates with the server 110 via a wireless network, the output port of the requester terminal 130 may be one or more antennas, which convert the electrical signal to electromagnetic signal. Similarly, a provider terminal 140 may receive an instruction and/or service request from the server 110 via electrical signal or electromagnet signals. Within an electronic device, such as the requester terminal 130, the provider terminal 140, and/or the server 110, when a processor thereof processes an instruction, transmits out an instruction, and/or performs an action, the instruction and/or action is conducted via electrical signals. For example, when the processor retrieves or saves data from a storage medium, it may transmit out electrical signals to a read/write device of the storage medium, which may read or write structured data in the storage medium. The structured data may be transmitted to the processor in the form of electrical signals via a bus of the electronic device. Here, an electrical signal may refer to one electrical signal, a series of electrical signals, and/or a plurality of discrete electrical signals.

FIG. 2 is a schematic diagram illustrating exemplary hardware and/or software components of a computing device according to some embodiments of the present disclosure.

In some embodiments, the computing device 200 may be a special purpose computer in some embodiments. The computing device 200 may be used to implement any component of the service system 100 as described herein. In some embodiments, the server 110, the requester terminal 130, and/or the provider terminal 140 may be implemented on the computing device 200. For example, the processing device 112 may be implemented on the computing device 200 and configured to perform functions of the processing device 112 disclosed in this disclosure. In FIGs. 1-2, only one such computer device is shown purely for convenience purposes. One of ordinary skill in the art would understood at the time of filing of this application that the computer functions relating to the service system 100 as described herein may be implemented in a distributed fashion on a number of similar platforms, to distribute the processing load.

The computing device 200 may include COM ports 250 that may connect with a network that may implement data communications. The computing device 200 may also include a processor 220, in the form of one or more processors (e.g., logic circuits) , for executing program instructions. For example, the processor 220 may include interface circuits and processing circuits therein. The interface circuits may be configured to receive electronic signals from a bus 210, wherein the electronic signals encode structured data and/or instructions for the processing circuits to process. The processing circuits may conduct logic calculations, and then determine a conclusion, a result, and/or an instruction encoded as electronic signals. Then the interface circuits may send out the electronic signals from the processing circuits via the bus 210.

The computing device 200 may further include program storage and data storage (e.g., a hard disk 270, a read-only memory (ROM) 230, a random-access memory (RAM) 240) for storing various data files applicable to computer processing and/or communication and/or program instructions executed possibly by the processor 220. The computing device 200 may also include an I/O device 260 that may support the input and output of data flows between computing device 200 and other components. Moreover, the computing device 200 may receive programs and data via the communication network.

Merely for illustration, only one processor is described in FIG. 2. Multiple processors are also contemplated, thus operations and/or method steps performed by one processor as described in the present disclosure may also be jointly or separately performed by the multiple processors. For example, if in the present disclosure the processor of the computing device 200 executes both step A and step B, it should be understood that step A and step B may also be performed by two different CPUs and/or processors jointly or separately in the computing device 200 (e.g., the first processor executes step A and the second processor executes step B, or the first and second processors jointly execute steps A and B) .

FIG. 3 is a schematic diagram illustrating exemplary hardware and/or software components of a mobile device according to some embodiments of the present disclosure. In some embodiments, the requester terminal 130 and/or the provider terminal 140 may be implemented on the mobile device 300. As illustrated in FIG. 3, the mobile device 300 may include a communication platform 310, a display 320, a graphics processing unit (GPU) 330, a central processing unit (CPU) 340, an I/O 350, a memory 360, a mobile operating system (OS) 370, application (s) 380, and a storage 390. In some embodiments, any other suitable component, including but not limited to a system bus or a controller (not shown) , may also be included in the mobile device 300.

In some embodiments, the mobile operating system 370 (e.g., iOS ^TM, Android ^TM, Windows Phone ^TM, etc. ) and one or more applications 380 may be loaded into the memory 360 from the storage 390 in order to be executed by the CPU 340. The applications 380 may include a browser or any other suitable mobile apps for receiving and rendering information relating to O2O services or other information from the service system 100. User interactions with the information stream may be achieved via the I/O 350 and provided to the storage device 160, the server 110 and/or other components of the service system 100.

To implement various modules, units, and their functionalities described in the present disclosure, computer hardware platforms may be used as the hardware platform (s) for one or more of the elements described herein. A computer with user interface elements may be used to implement a personal computer (PC) or any other type of work station or terminal device. A computer may also act as a system if appropriately programmed.

FIG. 4A and FIG. 4B are block diagrams illustrating exemplary processing devices according to some embodiments of the present disclosure. In some embodiments,

processing devices

112A and 112B may be embodiments of the processing device 112 as described in connection with FIG. 1.

In some embodiments, the processing device 112A may be configured to determine a day type of a target date and/or an operation strategy of a service platform (e.g., the service system 100) based on the day type of the target date. The processing device 112B may be configured to determine a loss function used in identifying a day type of a date (e.g., the target date) . In some embodiments, the

processing devices

112A and 112B may be implemented on the computing device 200 (e.g., the processor 220) illustrated in FIG. 2 or the CPU 340 illustrated in FIG. 3, respectively. Merely by way of example, the processing device 112A may be implemented on the CPU 340 of a mobile device and the processing device 112B may be implemented on the computing device 200. Alternatively, the

processing devices

112A and 112B may be implemented on the same computing device 200 or the same CPU 340.

The processing device 112A may include an obtaining module 402 and a determination module 404.

The obtaining module 402 may be configured to obtain information related to the service system 100 used in the determination of the day type of the target date and/or the determination of the operation strategy of the service platform. Exemplary information obtained by the obtaining module 402 may include overall operation data of the service platform associated with the target date, overall historical operation data of the service platform associated with one or more first historical dates (which is being of a certain day type and associated with the target date) , temporal information of the target date and/or the one or more first historical dates, or the like, or any combination thereof. More descriptions regarding the information obtained by the obtaining module 402 may be found elsewhere in the present disclosure. See, e.g., FIG. 5 and relevant descriptions thereof.

The determination module 404 may be configured to determine the day type of the target date based on the overall operation data and the overall historical operation data corresponding to a plurality of day types. For example, for each day type, the determination module 404 may determine a difference between the overall operation data and the corresponding overall historical operation data using a loss function, wherein an input of the loss function may include the overall operation data and the corresponding overall historical operation data. The determination module 404 may further determine the day type of the target data based on the differences corresponding to the plurality of day types. More descriptions regarding the determination of the day type of the target date may be found elsewhere in the present disclosure. See, e.g.,

operations

530 and 540 and relevant descriptions thereof.

In some embodiments, the determination module 404 may be further configured to determine an operation strategy with respect to at least one registered user terminal of the service platform based on the day type of the target date. The operation strategy may include, for example, a recommendation strategy, a dispatch strategy, a preferential strategy, or the like, or any combination thereof. More descriptions of the determination of the operation strategy may be found elsewhere in the present disclosure (e.g., operation 550 and the descriptions thereof) .

The processing device 112B may include an obtaining module 406 and a selection module 408.

The obtaining module 406 may be configured to obtain information used to determine the loss function for identifying a day type of a date (e.g., the target date) . Exemplary information obtained by the obtaining module 406 may include a day type of a sample target date, overall sample operation data of the service platform associated with the sample target date, overall sample historical operation data of the service platform associated with one or more first sample historical dates (which is being of a certain day type and associated with the sample target date) , a plurality of candidate loss functions, or the like, or any combination thereof. More descriptions regarding the information obtained by the obtaining module 406 may be found elsewhere in the present disclosure (e.g., FIG. 6 and relevant descriptions thereof) .

The selection module 408 may be configured to select the loss function among the plurality of candidate loss functions. In some embodiments, the selection module 408 may determine an accuracy score of each candidate loss function, and select the loss function based on the accuracy scores of the candidate loss functions. More descriptions regarding the selection of the loss function may be found elsewhere in the present disclosure. See, e.g., operation 640 and relevant descriptions thereof.

The modules may be hardware circuits of all or part of the processing device 112A and/or the processing device 112B. The modules may also be implemented as an application or set of instructions read and executed by the processing device 112A and/or the processing device 112B. Further, the modules may be any combination of the hardware circuits and the application/instructions. For example, the modules may be the part of the processing device 112A when the processing device 112A is executing the application/set of instructions.

It should be noted that the above descriptions of the

processing devices

112A and 112B are provided for the purposes of illustration, and is not intended to limit the scope of the present disclosure. For persons having ordinary skills in the art, multiple variations and modifications may be made under the teachings of the present disclosure. However, those variations and modifications do not depart from the scope of the present disclosure. In some embodiments, the processing device 112A and/or the processing device 112B may further include one or more additional modules (e.g., a storage module) . One or more modules of the processing device 112A and/or the processing device 112B described above may be omitted. In some embodiments, the

processing devices

112A and 112B may be integrated as a single processing device.

FIG. 5 is a flowchart illustrating an exemplary process for determining an operation strategy with respect to a registered user terminal of a service platform according to some embodiments of the present disclosure. In some embodiments, one or more operations of process 500 may be executed by the service system 100. For example, the process 500 may be implemented as a set of instructions (e.g., an application) stored in a storage device (e.g., the storage device 160, the ROM 230, the RAM 240, the storage 390) and invoked and/or executed by the processing device 112A (e.g., the processor 220 of the computing device 200, the CPU 340 of the mobile device 300, and/or the modules illustrated in FIG. 4A) . In some embodiments, the instructions may be transmitted in the form of electronic current or electrical signals. The operations of the illustrated process present below are intended to be illustrative. In some embodiments, the process 500 may be accomplished with one or more additional operations not described and/or without one or more of the operations herein discussed. Additionally, the order in which the operations of the process as illustrated in FIG. 5 and described below is not intended to be limiting.

The service platform may include any platform that provides one or more services to service requesters. The services provided by the service platform be any product as described elsewhere in this disclosure (e.g., FIG. 1 and the relevant descriptions) , such as but not limited to food, medicine, commodity, chemical product, electrical appliance, clothing, car, housing, luxury, a servicing product, a financial product, a knowledge product, an internet product. For illustration purposes, the present disclosure takes an O2O service as an example of the service provided by the service platform. It should be noted that this is not to be limiting, and the methods of the present disclosure may be applied to any other kind of services. Exemplary O2O services may include a transportation service (e.g., a taxi-hailing service, a chauffeur service, an express car service, a carpool service, a bus service, a driver hire service, and a shuttle service) , a meal delivery service, a delivery service, a shopping service, or the like, or any combination thereof.

In some embodiments, the service platform may be an Internet-based platform (e.g., the service system 100) that connects service requesters and the service providers through the Internet. The service requesters and the service providers may interact with the service platform via their user terminals, such as the requester terminals 130 and provider terminals 140. Normally, service demands of the service requesters may vary in different types of days (e.g., a working day, a rest day, a weekend, a holiday) . Taking passengers of an online transportation service system as an example, the passengers usually hail vehicles to their workplaces on workdays and to other places on weekends. Also, most of the passengers hail vehicles in morning and evening rush hours (e.g., 7: 00 a.m. to 9: 00 a.m. and 5: 00 p.m. to 7: 00 p.m. ) on workdays, while most of the passengers hail vehicles during, for example, 7: 00 p.m. to 10: 00 p.m. on weekends. On the other hand, the service providers of the service platform may need to meet different service demands on different types of days. Therefore, the service platform may need to adopt a specific operation strategy on a day with respect to the service requesters (or a specific service requester) and/or the service providers (or a specific service provider) according to a day type of the day. For illustration purposes, the following descriptions is provided with reference to determining a day type of a target day having a target date and to determining an operation strategy with respect to at least one user terminal registered on the service platform based on the day type of the target day.

In 510, the processing device 112A (e.g., the obtaining module 402) (e.g., the interface circuits of the processor 220) may obtain overall operation data of the service platform associated with the target date. The service platform may be configured to communicate with at least one user terminal (e.g., the requester terminal 130, the provider terminal 140) via a communication port (e.g., the COM ports 250) .

As used herein, the target date may refer to a date of the target day whose day type is to be determined. For example, the target date may be the date of the current day (e.g., today) or a future day (e.g., tomorrow, or any day after today) . In some embodiments, the target date may include the date of the target day on the solar calendar and/or the lunar calendar. The target date may include the month and the day of the target day. Alternatively, the target date may include the month, the day, and the year of the target date. For brevity, the term “target date” and “target day” are used interchangeably hereinafter.

The overall operation data of the service platform associated with the target date may refer to operation data of the service platform that can reflect or predict an overall operation status of the service platform in the target date or during a particular time period of the target date. For example, if the target date is the date of the current day, the overall operation data may include a total count (or number) or a total transaction amount of service orders that have been completed and/or are in progress, a total count (or number) of service requesters that have initiated a service order, a total count (or number) of service providers that have completed a service order in the service platform in the current day or during a particular period in the current day. The particular period in the current day may be any period that has been lapsed with respect to the present moment in the current day. For example, assuming the present moment is 10: 00 a.m., the particular time period may be, for example, three hours, four hours, or five hours before 10: 00 a.m.

As another example, if the target date is the date of a future day, the overall operation data may include a total count (or number) or a total transaction amount of reserved service orders, a total count (or number) of service requesters of the reserved service orders, a total count (or number) of service providers that have accepted the reserved service orders, wherein the reserve time of the reserved service orders may be in the future day or during a particular period in the future day. The particular period in the future day may be any period in the future day, for example, 7: 00 a.m. to 9: 00 a.m., 5: 00 p.m. to 7: 00 p.m., or 7: 00 p.m. to 10: 00 p.m. in the future day.

In some embodiments, the overall operation data may include a plurality of sets of operation data of the service platform in a plurality of time periods during the target date. Each set of the plurality of sets of operation data may correspond to a time period of the plurality of time periods. The plurality of time periods may be un-overlapping time periods in the target date or within the particular time period in the target date as described above. The time periods may be consecutive time periods or inconsecutive time periods. The lengths of the time periods may be the same as or different from each other. In some embodiments, the lengths of the time periods may be the same as each other, which are both equal to, for example, 10 minutes, 30 minutes, an hour, two hours, six hours, etc. Merely by way of example, the time periods may be three time periods, such as 18: 00 to 19: 00, 19: 00 to 20: 00, and 20: 00 to 21: 00 in the target date. The overall operation data may include a set of operation data of the service platform in each of the three time periods, such as a total count of completed or reserved service orders in each of the three time periods.

In some embodiments, the processing device 112A may obtain the overall operation data associated with the target date via the network 120 from one or more storage devices of the service system 100 that store operation data of the service system 100, such as the storage device 160, the ROM 230, and/or the RAM 240. Additionally or alternatively, the processing device 112A may obtain the overall operation data via the network 120 from an external source.

In 520, for each of a plurality of day types, the processing device 112A (e.g., the obtaining module 402) (e.g., the interface circuits of the processor 220) may obtain overall historical operation data of the service platform associated with one or more first historical dates. The one or more first historical dates corresponding to a day type may be of the day type and associated with the target date.

In some embodiments, the plurality of day types may include a working day and a rest day. As used herein, the working day may refer to an official working day in a country in which people need to work, normally including Monday to Friday. The rest day may refer to an official rest day in a country when people rest, normally including Saturday, Sunday and a holiday. The holiday may refer to an official holiday in a country. In some occasions, a day within Monday to Friday, which is often a workday, may actually be a rest day if it is within an official holiday. On the other hand, a day in a weekend, which is often a rest day, may be adjusted to a workday because of an official holiday close to the day. Therefore, in some embodiments, the working day may be further classified into a normal working day within Monday to Friday and an adjusted working day due to an official holiday. Additionally or alternatively, a rest day may be further classified into a weekend or a holiday. Optionally, the plurality of day types may further include a festival. The festival may refer to an official festival or unofficial festival in a country according to the solar calendar and/or the lunar calendar. Taking China as an example, the official festivals may include festivals in the Chinese lunar calendar, such as the Spring Festival, the Dragon Boat Festival, and the Mid-autumn Festival and also festivals in the solar calendar, such as the New Year’s Day, the International Labor Day, and the National day. Unofficial festivals in China may include a Shopping Festival (e.g., the double eleven shopping festival) , a Tourism Festival in a certain city, or the like, or any combination thereof. In some embodiments, the festival may be further classified into an official festival, an unofficial festival, a festival in the solar calendar, a festival in the lunar calendar, or the like, or any combination thereof. In some embodiments, the holiday and/or the festival may be further classified into a plurality of specific holidays and/or festivals in specific countries.

A historical date associated with the target date may refer to a historical date whose month and day is close to the month and day of the target date on the solar calendar and/or the lunar calendar. For example, if the target date is January 13, 2019 on the solar calendar (that is, December 8, 2018 on the lunar calendar) , a historical date A may be regarded as being associated with the target date if the difference between January 13 and the month and day of A on the solar calendar is smaller than a first number of days, such as 10 days, 20 days, a month, or the like. Additionally or alternatively, a historical date B may be regarded as being associated with the target date if the time difference from December 8 to the month and day of B on the lunar calendar is smaller than a second number of days, such as 10 days, 20 days, a month, or the like.

In some embodiments, the processing device 112A may obtain temporal information of the target date. The temporal information related to the target date may include a date of the target day on the lunar calendar, a date of the target day on the solar calendar date, solar term information (whether the target day is a particular solar term) , or the like, or any combination thereof. The processing device 112A may also obtain temporal information and day types of a plurality of third historical dates. The plurality of third historical dates may include any historical date before the target date. Particularly, in some embodiments, the plurality of third historical dates may include historical dates before the year of the target date. Further, for each of the day types, the processing device 112A may determine the one or more first historical dates being of the day type and associated with the target date among the plurality of third historical dates based on the temporal information of the target date, the temporal information of the third historical dates, and the day types of the third historical dates.

Merely by way of example, assuming that the target date on the solar calendar is January 6, 2019, the processing device 112A may obtain a corresponding date on the lunar calendar (i.e., December 1, 2018) and solar term information of the target date (i.e., the target day is not a particular solar term) . The processing device 112A may obtain temporal information and day types of a plurality of third historical dates before 2019. The processing device 112A may further determine, among the third historical dates, one or more working days associated with the target date and one or more rest days associated with the target date. Taking the working day (s) associated with the target date as an example, the working day (s) may include a working day whose month and day on the solar calendar is close to January 6 and/or a working day whose month and day on the lunar calendar is close to December 1. Merely by way of example, the working day (s) associated with the target date may include January 4, January 5, January 8, and January 9 in 2018.

For brevity, the overall historical operation data of the service platform associated with the one or more first historical dates corresponding to a day type may be referred to as first overall historical operation data. In some embodiments, the first overall historical operation data may include overall historical operation data of the service platform associated with each of the first historical date (s) . Taking a certain first historical date as an example, the overall historical operation data of the service platform associated with the first historical date may be similar to the overall operation data of the service platform associated with the target date as described in connection with operation 510. Merely by way of example, the overall operation data associated with the target date may include a total count completed service orders in the target date or during a particular period in the target date. Similarly, the overall historical operation data associated with the first historical date may include a total count of completed service orders in the first historical date or during the particular period in the first historical date. In some embodiments, the overall operation data may include a plurality of sets of operation data of the service platform in a plurality of time periods during the target date. Similarly, the overall historical operation data of the service platform associated with the first historical date may include a plurality of sets of historical operation data of the service platform in the plurality of time periods in the first historical date. Each set of historical operation data may correspond to a time period of the plurality of time periods.

In some embodiments, for a certain day type, the corresponding one or more first historical dates being of the day type associated with the target date may include a plurality of first historical dates. The first overall historical operation data may be an average or median of the overall historical operation data associated with each of the first historical dates. Merely by way of example, the overall historical operation data associated with each of the first historical dates may include a total count of service orders completed in the first historical date. The first overall historical operation data may include an average value of the total counts of service orders completed in the first historical dates. As another example, the overall historical operation data of each of the first historical dates may include total counts of service orders completed in a plurality of time periods in the first historical date. For each of the plurality of time periods, the first overall historical operation data may include an average value of the total counts of service orders completed in the time period in the first historical dates.

In some embodiments, the processing device 112A may obtain the overall historical operation data associated with the one or more first historical dates via the network 120 from one or more storage devices of the service system 100 that store operation data of the service system 100, such as the storage device 160, the ROM 230, and/or the RAM 240. Additionally or alternatively, the processing device 112A may obtain the overall historical operation data via the network 120 from an external source.

In 530, for each of the plurality of day types, the processing device 112A (e.g., the determination module 404) (e.g., the processing circuits of the processor 220) may determine a difference between the overall operation data and the corresponding overall historical operation data using a loss function, wherein an input of the loss function may include the overall operation data and the corresponding overall historical operation data.

As used herein, the loss function may also be referred to as a date classification model configured to identify a day type of a target date. In some embodiments, the loss function may identify the day type of a target date by measuring the difference between the overall operation data and the overall historical operation data corresponding to each day type. In some embodiments, as described in connection with operation 520, the overall operation data may include a plurality of sets of operation data in a plurality of time periods in the target date. For each day type, the corresponding overall historical operation data may include a plurality of sets of historical operation data in the time periods during one or more first historical date (s) , wherein the first historical date (s) may be of the day type and associated with the target date. Taking a certain day type as an example, the loss function may measure a difference between the sets of operation data of the target date and the sets of historical operation data in the corresponding first historical date (s) . The loss function may include a first component and a second component. The first component may be configured to determine, for each of the time periods, a difference between a set of operation data in the time period and the corresponding set of historical operation data in the time period. For example, for each time period, the first component may determine a difference value between the set operation data in the time period and the corresponding set of historical operation data in the time period, an absolute value of the difference value, a square of the difference value, a square root of the difference value, or any other suitable parameter measures the difference between the set of operation data and the corresponding set of operation data. As used herein, the loss function in which the first component determines the difference value, the absolute value of the difference value, the square of the difference value, and the square root of the difference value may be referred to as a linear loss function, an absolute loss function, a quadratic loss function, and a square root loss function, respectively. The second component may be configured to determine the difference between the overall operation data and the corresponding overall historical operation data based on the differences corresponding to the plurality of time periods. For example, the second component may determine a sum, an average value, or a median value of the differences corresponding to the plurality of time periods as the difference between the overall operation data and the corresponding overall historical operation data.

For illustration purposes, an example of a linear loss function is provided as an example. It is assumed that the overall operation data includes a first number of completed service orders, a second number of completed service orders, and a third number of completed service orders of the service platform in 18: 00 to 19: 00, 19: 00 to 20: 00, and 21: 00 to 22: 00 in the target date, respectively. The corresponding overall historical operation data may include a first historical number of completed service orders, a second historical number of completed service orders, and a third historical number of completed service orders of the service platform in 18: 00 to 19: 00, 19: 00 to 20: 00, and 21: 00 to 22: 00 in the one or more first historical dates, respectively. The first component of the loss function may determine a first difference value between the first number and the first historical number, a second difference value between the second number and the second historical number, and a third difference value between the third number and the third historical number. The second component may determine the difference between the overall operation data and the corresponding overall historical operation data by summing up the first difference value, the second difference value, and the third difference value.

In some embodiments, before inputting the overall operation data and the overall historical operation data corresponding to each day type into the loss function, the processing device 112A may determine an initial day type of the target date. For each day type, the processing device 112A may further determine the difference between the overall operation data and the corresponding overall historical operation data using the loss function, wherein an input to the loss function includes the overall operation data, the corresponding overall historical operation data, and the initial day type of the target date. In some embodiments, the processing device 112A may obtain one or more day types of one or more second historical dates associated with the target date. The one or more second historical dates associated with the target date may be similar to the historical date associated with target date as described in connection with operation 520, and the descriptions thereof are not repeated here. Further, the processing device 112A may determine the initial day type of the target date based on the day type (s) of the one or more second historical dates. For example, if most of the second historical date (s) are being of a certain day type, the processing device 112A may designate the certain day type as the initial day type of the target date.

In such cases, the second component of the loss function may further include a third component and a fourth component. For each of the day types, the third component may be configured to determine an initial difference between the overall operation data and the corresponding overall historical operation data. For example, the third component may determine a sum, an average value, or a median value of the differences corresponding to the plurality of time periods determined by the first component. The fourth component may be configured to determine the difference between the overall operation data and the corresponding overall historical operation data based on the initial difference and the initial day type of the target date. For example, the fourth component may determine the difference between the overall operation data and the corresponding overall historical operation data by adding a first adjustment coefficient associated with the initial day type to the initial difference or subtracting a second adjustment coefficient with the initial day type from the initial difference.

In some embodiments, the loss function may be previously determined by the processing device 112A or another computing device and stored in a storage device (e.g., the storage device 160) in the service system 100. For example, the loss function may be determined by the processing device 112B according to a loss function determination process (e.g., a process including one or more operations of process 600 as described in connection with FIG. 6 and/or one or more operations of process 700 as described in connection with FIG. 7) . Alternatively, the loss function may be obtained from an external source via the network 120. In some embodiments, the loss function may be determined based on machine learning technique. The machine learning technique may determine or build the loss function based on analysis on sample data (normally a large number of sample data) , making the loss function being reliable and accurate.

In 540, the processing device 112A (e.g., the determination module 404) (e.g., the processing circuits of the processor 220) may determine the day type of the target date based on the differences corresponding to the plurality of day types.

In some embodiments, the processing device 112A may rank the day types based on the respective differences according to a predetermined order (e.g., an ascending order, a descending order) . Further, the processing device 112A may determine a day type from the day types based on the ranking result. For example, the day types are ranked based on the respective differences in an ascending order, and the day type ranked first on the ranking result is designated as the day type of the target date.

In 550, the processing device 112A (e.g., the determination module 404) (e.g., the processing circuits of the processor 220) may determine an operation strategy with respect to the at least one registered user terminal of the service platform based on the day type of the target date. The operation strategy may include, for example, a recommendation strategy, a dispatch strategy, a preferential strategy, or the like, or any combination thereof.

The recommendation strategy may refer to a strategy to recommend information to a user of the at least one registered user terminal. Exemplary recommended information may include a recommended service or product, a recommended location (e.g., a recommended start location or pick-up location for a transportation service) , a recommended piece of news, a recommended promotion or discount, a recommended service provider (e.g., a recommended restaurant for a meal delivery service) , or the like, or any combination thereof. In some embodiments, the processing device 112A may determine different recommended information for the user according to the day type of the target date. Merely by way of example, for a meal booking service system, the processing device 112A may determine one or more restaurants suitable for lovers as the recommended information if the target date is a Valentine’s Day. As another example, for a transportation service system, the workplace of the user may be determined as the recommended information if the target date is a working day.

In some embodiments, the recommended information may be determined by taking preference (also referred to as user behavior herein) of the user in the target date into consideration. For example, the processing device 112A may obtain preference information relating to the user according to the day type of the target date. The preference information may reflect a preference of the user in days having the same day type as the target date. Taking a transportation service system as an example, assuming that the target date is a rest day, the preference information relating to the user may include the most frequently used type of transportation service, start location, and/or pick-up location of the user in rest days, a period in which the user hails a vehicle frequently (e.g., for more than a certain number of time in a month) during rest days, or the like, or any combination thereof. In some embodiments, the preference of the user in a certain type of days may be determined by analyzing historical consumption information of the user.

Further, the processing device 112A may determine a first message for presentation on the at least one registered user terminal based on the preference information relating to the user. The first message may include recommended information which suits the preference of the user. For example, if the preference information indicates that the user normally hails a vehicle to a shopping mall during 18: 00 to 19: 00 in rest days, the processing device 112A may determine the first message as “Do you want to go to the shopping mall now? ” , wherein optionally, the first message may be transmitted to the at least one registered user terminal at a time point close to 18: 00 (e.g., 17: 50) in the target date.

The dispatch strategy may refer to a strategy for a transportation service system to dispatch the user to a specific location or in a specific period. Normally, the transportation service system may have different hot service regions and hot service periods in different types of days. As used herein, a region may be regarded as a hot service region if the number of historical service orders whose start locations and/or destinations are within the region is greater than a first threshold. Additionally or alternatively, a region may be regarded as a hot service region if the number of service providers and/or service requesters in the region is greater than a second threshold. A period in a day may be regarded as a hot service period if the number of historical service orders in started or completed in the period is greater than a third threshold. Additionally or alternatively, a period in a day may be regarded as a hot service period if the number of service providers requesting services and/or service requesters providing services in the period is greater than a fourth threshold.

In some embodiments, the processing device 112A may determine the dispatch strategy of the target date based on the day type of the target date. For example, the processing device 112A may determine or obtain one or more hot service regions and/or one or more hot service periods in days having the same day type as the target date. The processing device 112A may further determine the dispatch strategy of the target date based on the hot service region (s) and/or the hot service period (s) . Merely by way of example, if the user of the at least one user terminal is a passenger, the dispatch strategy may be used to dispatch the passenger to a service region other than the hot service region (s) or dispatch the passenger to initiate a service order in a period other than the hot service period (s) . If the user of the at least one terminal is a driver, the dispatch strategy may be used to dispatch the driver to the hot service region (s) or dispatch the driver to provide services in the hot service period (s) . In some embodiments, the processing device 112A may further transmit a second message for presentation on the at least one user terminal based on the dispatch strategy. The second message may include, for example, traffic condition information, an advice for the user, a coupon which is valid in regions other than the hot service regions and/or periods other than the hot service periods. In some embodiments, the dispatch strategy may also be referred to as a traffic monitoring strategy.

The preferential strategy may refer to a strategy for providing preferential information to the user. Exemplary preferential information may include discount information related to a service provider (e.g., a discount of a particular restaurant for a meal delivery service in the target day) , coupon information (e.g., a coupon for a transportation service which is valid in target day) , or the like, or any combination thereof. In some embodiments, the processing device 112A may determine different preferential information for the user according to the day type of the target date. Merely by way of example, for a transportation service system, the processing device 112A may determine and send one or more coupons (e.g., one or more carpool coupons that can be used in morning and evening rush hours) as the preferential information if the target date is a working day.

It should be noted that the above description regarding the process 500 is merely provided for the purposes of illustration, and not intended to limit the scope of the present disclosure. For persons having ordinary skills in the art, multiple variations and modifications may be made under the teachings of the present disclosure. However, those variations and modifications do not depart from the scope of the present disclosure. In some embodiments, one or more operations may be omitted and/or one or more additional operations may be added. For example, the process 500 may further include a storing operation in which the processing device 112A stores the day type of the target date in a storage device (e.g., the storage device 160) of the service system 100. Optionally, the target date may be stored as a sample target date in the storage device, wherein the sample target date and the corresponding day type may be used in a determination and/or a validation of a loss function for identifying a day type of a date.

In some embodiments, the plurality of day types may include a working day and a rest day. If the target date is determined to be the rest day, the processing device 112A may obtain temporal information of the target date. The processing device 112A may further determine whether the target date is related to a festival based on the temporal information of the target date. For example, the processing device 112A may determine whether the month and day of the target date on the solar or lunar calendar is close to a specific festival (e.g., the time difference between the month and day and the specific festival being smaller than a certain number of days) . In response to a determination that the month and day of the target date is close to the specific festival, the processing device 112A may determine that the target date is associated with the festival. Further, in some embodiments, the processing device 112A may determine a particular operation strategy corresponding to the specific festival as described in connection with 550.

FIG. 6 is a flowchart illustrating an exemplary process for determining a loss function used in identifying a day type of a date according to some embodiments of the present disclosure. In some embodiments, one or more operations of process 600 may be executed by the service system 100. For example, the process 600 may be implemented as a set of instructions (e.g., an application) stored in a storage device (e.g., the storage device 160, the ROM 230, the RAM 240, the storage 390) and invoked and/or executed by the processing device 112B (e.g., the processor 220 of the computing device 200, the CPU 340 of the mobile device 300, and/or the modules illustrated in FIG. 4B) . In some embodiments, the instructions may be transmitted in the form of electronic current or electrical signals. The operations of the illustrated process present below are intended to be illustrative. In some embodiments, the process 600 may be accomplished with one or more additional operations not described and/or without one or more of the operations herein discussed. Additionally, the order in which the operations of the process as illustrated in FIG. 6 and described below is not intended to be limiting. In some embodiments, one or more operations of the process 600 may be performed to achieve at least part of the operation 530 as described in connection with FIG. 5.

In 610, the processing device 112B (e.g., the obtaining module 406) (e.g., the interface circuits of the processor 220) may obtain a day type of a sample target date and overall sample operation data of a service platform associated with the sample target date.

As used herein, the sample target date may refer to a date having a known day type which is used as a sample in the determination of the loss function. In some embodiments, the day type of the sample target date may be one of a working day, a rest day, a weekend, a holiday, a festival, or the like. The overall sample operation data of the service platform associated with the sample target date may refer to operation data of the service platform that can reflect an overall operation status of the service platform in the sample target date or during a particular time period of the sample target date. The overall sample operation data may be similar to the overall operation data of the service platform associated with the target date as described in connection with operation 510, and the descriptions thereof are not repeated here. In some embodiments, the overall sample operation data may include a plurality of sets of sample operation data in a plurality of time periods during the sample target date. The sets of sample operation data may be similar to the sets of operation data of the service platform associated with the target date as described in connection with operation 510, and the descriptions thereof are not repeated here.

In 620, for each of a plurality of day types, the processing device 112B (e.g., the obtaining module 406) (e.g., the interface circuits of the processor 220) may obtain overall sample historical operation data of the service platform associated with one or more first sample historical dates. The one or more first sample historical dates corresponding to a day type may be of the day type and associated with the sample target date.

For a specific day type, the corresponding first sample historical date (s) being of the day type and associated with the sample target date may be similar to the first historical date (s) being of the day type and associated with the target date as described in connection with operation 520. The overall sample historical operation associated with the corresponding first sample historical date (s) may be similar to the overall historical operation data associated with the corresponding first historical date (s) as described in connection with operation 520. In some embodiments, for each of the day types, the corresponding overall sample historical operation data may include a plurality of sets of sample historical operation data in a plurality of time periods during the corresponding first sample historical date (s) . Each of the sets of sample historical operation data may correspond to one of the plurality of time periods. The sets of sample historical operation data may be similar to the sets of historical operation data of the service platform associated with the first historical date (s) corresponding to the day type as described in connection with operation 520, and the descriptions thereof are not repeated.

In 630, the processing device 112B (e.g., the obtaining module 406) (e.g., the interface circuits of the processor 220) may obtain a plurality of candidate loss functions. The plurality of candidate loss functions may include a plurality of types of loss functions, such as, a linear loss function, an absolute loss function, a quadratic loss function, a square root loss function, or the like, or any combination thereof. More descriptions regarding the different types of loss functions may be found elsewhere in the present disclosure (e.g., FIG. 5 and relevant descriptions thereof) . Additionally or alternatively, the candidate loss functions may include two or more candidate loss functions, which are of the same type of loss function and have different parameters (e.g., different adjustment coefficients as described in connection with operation 530) .

In 640, the processing device 112B (e.g., the selection module 408) (e.g., the processing circuits of the processor 220) may select a loss function among the plurality of candidate loss functions based at least in part on the overall sample operation data, the day type of the sample target date, and the overall sample historical operation data corresponding to the plurality of day types.

In some embodiments, the processing device 112B may determine an accuracy score of each candidate loss function based on the overall operation data, the day type of the sample target date, and the overall sample historical operation data corresponding to the plurality of day types. The processing device 112B may further select the loss function based on the accuracy scores of the candidate loss functions. Merely by way of example, the candidate loss function having the highest accuracy score may be selected as the loss function. In some embodiments, the processing device 112B may perform one or more operations in process 700 as described in connection with FIG. 7 to select the loss function among the candidate loss functions. In some embodiments, the selected loss function may be used in determining a day type of a target date, for example, used in the process 500 as described in connection with FIG. 5.

It should be noted that the above description of the process 600 is merely provided for the purposes of illustration, and not intended to limit the scope of the present disclosure. For persons having ordinary skills in the art, multiple variations and modifications may be made under the teachings of the present disclosure. However, those variations and modifications do not depart from the scope of the present disclosure. In some embodiments, one or more operations may be omitted and/or one or more additional operations may be added. For example,

operations

610 and 620 may be combined into a single operation. As another example, a validation operation may be added after operation 640 to validate the loss function. In some embodiments, in operation 610, the processing device 112B may obtain day types of a plurality of sample target dates and overall sample operation data of the service platform associated with each of the sample target dates. The processing device 112B may further perform operation 620 for each of the sample target dates to obtain overall sample historical operation data corresponding to the sample target date. In 640, the processing device 112B may select the loss function based on the overall sample operation data and the overall sample historical operation data corresponding to each of the sample target dates.

FIG. 7 is a flowchart illustrating an exemplary process for selecting a loss function among a plurality of candidate loss functions according to some embodiments of the present disclosure. In some embodiments, one or more operations of process 700 may be executed by the service system 100. For example, the process 700 may be implemented as a set of instructions (e.g., an application) stored in a storage device (e.g., the storage device 160, the ROM 230, the RAM 240, the storage 390) and invoked and/or executed by the processing device 112B (e.g., the processor 220 of the computing device 200, the CPU 340 of the mobile device 300, and/or the modules illustrated in FIG. 4B) . In some embodiments, the instructions may be transmitted in the form of electronic current or electrical signals. The operations of the illustrated process present below are intended to be illustrative. In some embodiments, the process 700 may be accomplished with one or more additional operations not described and/or without one or more of the operations herein discussed. Additionally, the order in which the operations of the process as illustrated in FIG. 7 and described below is not intended to be limiting. In some embodiments, one or more operations of the process 700 may be performed to achieve at least part of the operation 640 as described in connection with FIG. 6.

In 710, for each of the candidate loss functions, the processing device 112B (e.g., the selection module 408) (e.g., the processing circuits of the processor 220) may determine a predicted day type of the sample target date using the candidate loss function based on the overall sample operation data and the overall sample historical operation data corresponding to the day types.

For illustration purposes, the following description is provided with reference to determining the predicted day type of the sample target date using a candidate loss function. In some embodiments, the determination of the predicted day type of the sample target date using the candidate loss function may be similar to the determination of the day type of the target date using the loss function as described in connection with

operations

530 and 540. For example, for each day type, the processing device 112B may determine a sample difference between the overall sample operation data and the corresponding overall sample historical operation data using the candidate loss function, wherein an input of the candidate loss function may include the overall sample operation data and the overall sample historical operation data corresponding to the day type. For each day type, the sample difference between the overall sample operation data and the corresponding overall sample historical operation data may be similar to the difference between the overall operation data and the corresponding overall historical operation data as described in connection with operation 530. The processing device 112B may further determine the predicted day type of the sample target date based on the sample differences corresponding to the day types. For example, processing device 112B may designate a day type whose corresponding difference is the smallest among the day types as the predicted type of the sample target date.

In some embodiments, the overall sample operation data may include a plurality of sets of sample operation data in a plurality of time periods during the sample target date. For each day type, the corresponding overall sample historical operation data may include a plurality of sets of sample historical operation data in the time periods during the corresponding first sample historical date (s) . The candidate loss function may include a first component and a second component. For each of time periods, the first component may be configured to determine a first sample difference between a set of sample operation data in the time period and the corresponding set of sample historical operation data in the time period. The second component may be configured to determine the sample difference between the overall sample operation data and the overall sample historical operation data corresponding to the day type based on the first sample differences corresponding to the time periods. The first and second components of the candidate loss function may be similar to that of the loss function, respectively, and the descriptions thereof are not repeated.

In some embodiments, before inputting the overall sample operation data and the overall sample historical operation data into the candidate loss function, the processing device 112B may further determine an initial day type of the sample target date. For each of the day type, the processing device 112B may further determine the sample difference between the overall sample operation data and the corresponding overall sample historical operation data using the candidate loss function, wherein an input of the candidate loss function may include the overall sample operation data, the corresponding overall sample historical operation data, and the initial day type of the sample target date. In some embodiments, the determination of the initial day type of the sample target date may be similar to the determination of the initial day type of the target date as described in connection with 530. For example, the processing device 112B may obtain one or more day types of one or more sample second historical dates associated with the sample target date. The processing device 112B may further determine the initial day type of the sample target date based on the day type (s) of the sample second historical date (s) . In such cases, in some embodiments, the second component of the candidate loss function may further include a third component and a fourth component, which is similar to the third component and the fourth component of the loss function, respectively, as described in connection with operation 530.

In 720, for each of the candidate loss functions, the processing device 112B (e.g., the selection module 408) (e.g., the processing circuits of the processor 220) may determine an accuracy score of the candidate loss function based at least in part on the predicted day type and the day type of the sample target date.

For illustration purposes, the following description is provided with reference to determining the accuracy score of a candidate loss function. The accuracy score of the candidate loss function may indicate an accuracy of the candidate loss function for identifying a day type of a date. In some embodiments, the processing device 112B may determine whether the predicted day type determined based on the candidate loss function is the same as the known day type of the sample target date. If it is determined that the corresponding predicted day type is the same as the known day type of the sample target date, the processing device 112B may designate a first accuracy score to the candidate loss function. On the other hand, if it is determined that the corresponding predicted day type is different from the known day type of the sample target date, the processing device 112B may designate a second accuracy score to the candidate loss function, wherein the second accuracy score is lower than the first accuracy score.

In some embodiments, as described in connection with FIG. 6, the processing device 112B may obtain a day type, overall sample operation data, and overall sample historical operation data for a plurality of sample target dates. For each of the sample target dates, the processing device 112B may perform operation 710 to determine a predicted day type of the sample target date using the candidate loss function. In 720, the processing device 112B may determine an accuracy score of the candidate loss function based on the corresponding predicted day types and the actual day types of the sample target dates. For example, the processing device 112B may determine, for each sample target date, whether the predicted day type of the sample target date determined by the candidate loss function is the same as the known day type of the sample target date. If the predicted day type is the same as the known day type of the sample target date, the sample target date may be considered as a positive sample target date corresponding to the candidate loss function. The processing device 112B may further determine a ratio of the positive sample target date (s) to the sample target dates as the accuracy sore of the candidate loss function.

In 730, the processing device 112B (e.g., the selection module 408) (e.g., the processing circuits of the processor 220) may select the candidate loss function having the highest accuracy score among the candidate loss functions as the loss function. For example, the processing device 112B may rank the candidate loss functions based on the respective accuracy scores in a descending order. Further, the processing device 112B may determine the candidate loss function ranked first on the ranking result as the loss function.

It should be noted that the above description of the process 700 is merely provided for the purposes of illustration, and not intended to limit the scope of the present disclosure. For persons having ordinary skills in the art, multiple variations and modifications may be made under the teachings of the present disclosure. However, those variations and modifications do not depart from the scope of the present disclosure. In some embodiments, one or more operations may be omitted and/or one or more additional operations may be added. For example, a validation operation may be added after operation 730 to validate the selected loss function.

FIG. 8 is a block diagram illustrating exemplary processing device according to some embodiments of the present disclosure. As shown in FIG. 4, the processing engine 112 may include a model construction module 802, a determination module 804, and a recommendation module 806.

The model construction model 802 may be configured to construct a date classification model using information and date types of a plurality of historical dates. The date classification model may be used to determine a day type of a certain date. Details regarding the construction of the date classification model may be found elsewhere in the present disclosure (e.g., operation 910 in FIG. 9 and the relevant descriptions thereof) .

The determination module 804 may be configured to determine a day type of a target date based on the date classification model and information related to the target date. As used herein, the target date may refer to a date of a target day whose day type is to be determined. In some embodiments, the determination module 804 may determine the day type of the target date by inputting the information related to the target date into the date classification model. Details regarding determination of the day type of the target date may be found elsewhere in the present disclosure (e.g., operation 920 in FIG. 9 and the relevant descriptions thereof) .

The recommendation module 806 may be configured to recommend information a user according to the day type of the target date. Exemplary recommended information may include, for example, a recommended service or product, a recommended location (e.g., a recommended start location or pick-up location for a transportation service) , a recommended piece of news, a recommended promotion or discount, a recommended service provider (e.g., a recommended restaurant for a meal delivery service) , or the like, or any combination thereof. Details regarding the recommendation of the information may be found elsewhere in the present disclosure (e.g., operation 930 in FIG. 9 and the relevant descriptions thereof) .

The modules may be hardware circuits of all or part of the processing device 112. The modules may also be implemented as an application or set of instructions read and executed by the processing device 112. Further, the modules may be any combination of the hardware circuits and the application/instructions. For example, the modules may be the part of the processing device 112 when the processing device 112 is executing the application/set of instructions. It should be noted that the above descriptions of the processing device 112 are provided for the purposes of illustration, and is not intended to limit the scope of the present disclosure. For persons having ordinary skills in the art, multiple variations and modifications may be made under the teachings of the present disclosure. However, those variations and modifications do not depart from the scope of the present disclosure. In some embodiments, the processing device 112 may further include one or more additional modules (e.g., a storage module) . One or more modules of the processing device 112 described above may be omitted.

FIG. 9 is a flowchart illustrating an exemplary process for recommending information to a user based on a day type of a target date according to some embodiments of the present disclosure. In some embodiments, one or more operations of process 900 may be executed by the service system 100. For example, the process 900 may be implemented as a set of instructions (e.g., an application) stored in a storage device (e.g., the storage device 160, the ROM 230, the RAM 240, the storage 390) and invoked and/or executed by the processing device 112 (e.g., the processor 220 of the computing device 200, the CPU 340 of the mobile device 300, and/or the modules illustrated in FIG. 8) . In some embodiments, the instructions may be transmitted in the form of electronic current or electrical signals. The operations of the illustrated process present below are intended to be illustrative. In some embodiments, the process 900 may be accomplished with one or more additional operations not described and/or without one or more of the operations herein discussed. Additionally, the order in which the operations of the process as illustrated in FIG. 9 and described below is not intended to be limiting.

In 910, the processing device 112 (e.g., the model construction module 802) (e.g., the processing circuits of the processor 220) may construct a date classification model using information and date types of a plurality of historical dates.

The date classification model may be used to determine a day type of a certain date. The information related to a historical date may include, for example, temporal information of the historical date, overall historical operation data of a service system (e.g., the service system 100) associated with the historical date, or the like. The day type of a historical date may be, for example, a working day, a rest day, a weekend, a holiday, a festival, or the like, or any combination thereof. Details regarding the temporal information, the overall historical operation data, and the day type may be found elsewhere in the present disclosure (e.g., FIG. 5 and the relevant descriptions thereof) .

In some embodiments, the processing device 112 may obtain one or more preliminary loss functions (also referred to as candidate loss functions herein) . The processing device 112 may further construct the date classification model by training the one or more preliminary loss functions using the information and the date types of the plurality of historical dates. In some embodiments, the processing device 112 may construct the date classification model by performing one or more operations of the process 700 as described in connection with FIG. 7.

In 920, the processing device 112 (e.g., the determination module 804) (e.g., the processing circuits of the processor 220) may determine a day type of a target date based on the date classification model and information related to the target date.

As used herein, a target date may refer to the date of a target day whose day type is to be determined. For example, the target date may be the date of the current day (e.g., today) or a future day (e.g., tomorrow, or any day after today) . The information related to the target date may include, for example, a date of the target day on the lunar calendar, a date of the target day on the solar calendar date, overall operation data of the service platform associated with the target date, or the like, or any combination thereof. In some embodiments, the processing device 112 may determine the day type of the target date by inputting the information related to the target date into the date classification model.

In 930, the processing device 112 (e.g., the recommendation module 806) (e.g., the processing circuits of the processor 220) may recommend information to the user according to the day type of the target date.

Exemplary recommended information may include, for example, a recommended service or product, a recommended location (e.g., a recommended start location or pick-up location for a transportation service) , a recommended piece of news, a recommended promotion or discount, a recommended service provider (e.g., a recommended restaurant for a meal delivery service) , or the like, or any combination thereof. In some embodiments, the processing device 112 may transmit the recommended information to a user terminal of the user for presentation.

In some embodiments, the recommended information may include traffic monitoring (or dispatch) information, such as traffic condition information (e.g., a traffic condition in a region where the user is located) , a dispatch message to dispatch the user to a specific location or in a specific period, or the like. In some embodiments, the processing device 112 may obtain a plurality of traffic monitoring strategies corresponding to a plurality of day types. A traffic monitoring strategy corresponding to a certain day type may refer to a strategy for a transportation service system to monitor a traffic condition and/or to dispatch users on days having the certain day type. Normally, the transportation service system may have different hot service regions and hot service periods in different types of days. The transportation service system may need to adopt different traffic monitoring strategies in different types of days. In some embodiments, the traffic monitoring strategies may be preset by a user of the transportation service system or determined based historical service data of the transportation service system. The traffic monitoring strategies corresponding to the plurality of day types may be stored in a storage device of the service system 100 and be retrieved by the processing device 112. The processing device 112 may then determine a traffic monitoring strategy corresponding to the day type of the target date among the plurality of traffic monitoring strategies. The processing device 112 may further implement the traffic monitoring strategy corresponding to the day type of the target date and/or recommend traffic monitoring information to the user.

In some embodiments, the processing device 112 may determine a user behavior (or preference) of the user on the target date based on historical consumption information of the user and the day type of the target date. For example, the processing device 112 obtain historical consumption information of the user in historical days having the same day type as the target date, and determine the user behavior (or preference) of the user on the target date by analyzing the historical consumption information. The processing device 112 may further recommend information to the user based on the user behavior (or preference) of the user on the target date.

It should be noted that the above description of the process 900 is merely provided for the purposes of illustration, and not intended to limit the scope of the present disclosure. For persons having ordinary skills in the art, multiple variations and modifications may be made under the teachings of the present disclosure. However, those variations and modifications do not depart from the scope of the present disclosure.

Having thus described the basic concepts, it may be rather apparent to those skilled in the art after reading this detailed disclosure that the foregoing detailed disclosure is intended to be presented by way of example only and is not limiting. Various alterations, improvements, and modifications may occur and are intended to those skilled in the art, though not expressly stated herein. These alterations, improvements, and modifications are intended to be suggested by this disclosure, and are within the spirit and scope of the exemplary embodiments of this disclosure.

Moreover, certain terminology has been used to describe embodiments of the present disclosure. For example, the terms “one embodiment, ” “an embodiment, ” and/or “some embodiments” mean that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment of the present disclosure. Therefore, it is emphasized and should be appreciated that two or more references to “an embodiment, ” “one embodiment, ” or “an alternative embodiment” in various portions of this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures or characteristics may be combined as suitable in one or more embodiments of the present disclosure.

Further, it will be appreciated by one skilled in the art, aspects of the present disclosure may be illustrated and described herein in any of a number of patentable classes or context including any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof. Accordingly, aspects of the present disclosure may be implemented entirely hardware, entirely software (including firmware, resident software, micro-code, etc. ) or combining software and hardware implementation that may all generally be referred to herein as a "block, " “module, ” “engine, ” “unit, ” “component, ” or “system. ” Furthermore, aspects of the present disclosure may take the form of a computer program product embodied in one or more computer readable media having computer readable program code embodied thereon.

A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated signal may take any of a variety of forms, including electro-magnetic, optical, or the like, or any suitable combination thereof. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that may communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable signal medium may be transmitted using any appropriate medium, including wireless, wireline, optical fiber cable, RF, or the like, or any suitable combination of the foregoing.

Computer program code for carrying out operations for aspects of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C++, C#, VB. NET, Python or the like, conventional procedural programming languages, such as the “C” programming language, Visual Basic, Fortran 1703, Perl, COBOL 1702, PHP, ABAP, dynamic programming languages such as Python, Ruby and Groovy, or other programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN) , or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider) or in a cloud computing environment or offered as a service such as a software as a service (SaaS) .

Furthermore, the recited order of processing elements or sequences, or the use of numbers, letters, or other designations, therefore, is not intended to limit the claimed processes and methods to any order except as may be specified in the claims. Although the above disclosure discusses through various examples what is currently considered to be a variety of useful embodiments of the disclosure, it is to be understood that such detail is solely for that purpose, and that the appended claims are not limited to the disclosed embodiments, but, on the contrary, are intended to cover modifications and equivalent arrangements that are within the spirit and scope of the disclosed embodiments. For example, although the implementation of various components described above may be embodied in a hardware device, it may also be implemented as a software-only solution-e.g., an installation on an existing server or mobile device.

Similarly, it should be appreciated that in the foregoing description of embodiments of the present disclosure, various features are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure aiding in the understanding of one or more of the various embodiments. This method of disclosure, however, is not to be interpreted as reflecting an intention that the claimed subject matter requires more features than are expressly recited in each claim. Rather, claimed subject matter may lie in less than all features of a single foregoing disclosed embodiment.

1. A system for determining a day type of a target date among a plurality of day types, comprising:

a communication port communicatively connected to a network;

at least one storage medium including a set of instructions; and

at least one processor in communication with the communication port and the at least one storage medium, wherein when executing the instructions, the at least one processor is configured to direct the system to perform operations including:

obtaining overall operation data of a service platform associated with the target date, the service platform configured to communicate, via the communication port, with at least one registered user terminal;

for each of the plurality of day types, obtaining overall historical operation data of the service platform associated with one or more first historical dates, the one or more first historical dates being of the day type and associated with the target date;

for each of the plurality of day types, determining a difference between the overall operation data and the corresponding overall historical operation data using a loss function, wherein an input to the loss function includes the overall operation data and the corresponding overall historical operation data;

determining, based on the differences corresponding to the plurality of day types, the day type of the target date; and

determining, based on the day type of the target date, an operation strategy with respect to the registered user terminal of the service platform.

2. The system of item 1, wherein:

the overall operation data includes a plurality of sets of operation data of the service platform in a plurality of time periods during the target date, each of the plurality of sets of operation data corresponding to one of the plurality of time periods, and

for each of the plurality of day types, the corresponding overall historical operation data includes a plurality of sets of historical operation data of the service platform in the plurality of time periods during the one or more first historical dates, each of the plurality of sets of historical operation data corresponding to one of the plurality of time periods.

3. The system of item 2, the loss function comprising a first component and a second component, wherein:

for each of the plurality of day types,

the first component is configured to determine, for each of plurality of time periods, a first difference between a set of operation data of the time period and the corresponding set of historical operation data of the time period, and

the second component is configured to determine the difference between the overall operation data and the corresponding overall historical operation data based on the first differences corresponding to the plurality of time periods.

4. The system of any one of items 1 to 3, wherein for each of the plurality of day types, to determine a difference between the overall operation data and the corresponding overall historical operation data using a loss function, the at least one processor is further configured to direct the system to perform additional operations including:

obtaining one or more day types of one or more second historical dates associated with the target date;

determining, based on the one or more day types of the one or more second historical dates, an initial day type of the target date; and

for the day type, determining the difference between the overall operation data and the corresponding overall historical operation data using the loss function, wherein an input to the loss function includes the overall operation data, the corresponding overall historical operation data, and the initial day type of the target date.

5. The system of item 4, the loss function comprising a third component and a fourth component, wherein:

for each of the plurality of day types,

the third component is configured to determine an initial difference between the overall operation data and the corresponding overall historical operation data, and

the fourth component is configured to determine, based on the initial difference and the initial day type of the target date, the difference between the overall operation data and the corresponding overall historical operation data.

6. The system of item 1, wherein the at least one processor is further configured to direct the system to perform additional operations including:

obtaining temporal information of the target date;

obtaining temporal information and day types of a plurality of third historical dates; and

for each of the plurality of day types, determining, based on the temporal information of the target date, the temporal information of the plurality of third historical dates, and the day types of the plurality of third historical dates, the one or more first historical dates being of the day type and associated with the target date among the plurality of third historical dates.

7. The system of item 1, wherein the at least one processor is further configured to direct the system to perform additional operations including:

determining that the target date is a rest day; and

in response to a determination that the target date is a rest day,

obtaining temporal information of the target date; and

determining whether the target date relates to a festival based on the temporal information of the target date.

8. The system of any one of items 1 to 7, wherein the loss function is at least one of a linear loss function, an absolute loss function, a quadratic loss function, or a square root loss function.

9. The system of any one of items 1 to 8, wherein the day type of the target date is at least one of a working day, a rest day, a weekend, a holiday, or a festival.

10. The system of any one of items 1 to 9, wherein to determine an operation strategy with respect to the registered user terminal of the service platform based on the day type of the target date, the at least one processor is further configured to direct the system to perform additional operations including:

obtaining preference information relating to a user of the at least one registered user terminal according to the day type of the target date; and

determining, based on the preference information relating to the user, a message for presentation on the at least one registered user terminal.

11. The system of any one of items 1 to 10, wherein to determine an operation strategy with respect to the registered user terminal of the service platform based on the day type of the target date, the at least one processor is further configured to direct the system to perform additional operations including:

determining, based on the day type of the target date, a strategy for dispatching a user of the at least one registered user terminal on the target date.

12. The system of any one of items 1 to 11, wherein the loss function is determined according to a loss function determination process, the loss function determination process including:

obtaining overall sample operation data associated with a sample target date and a day type of the sample target date;

for each of the plurality of day types, obtaining overall sample historical operation data associated with one or more sample historical dates, the one or more sample historical dates being of the day type and associated with the sample target date;

obtaining a plurality of candidate loss functions; and

selecting, from the plurality of candidate loss functions, the loss function based at least in part on the overall sample operation data, the day type of the sample target date, and the overall sample historical operation data corresponding to the plurality of day types.

13. A method for determining a day type of a target date among a plurality of day types, comprising:

obtaining overall operation data of a service platform associated with the target date, the service platform configured to communicate with, via the communication port, at least one registered user terminal;

for each of the plurality of day types, obtaining, overall historical operation data of the service platform associated with one or more first historical dates, the one or more first historical dates being of the day type and associated with the target date;

14. The method of item 13, wherein:

15. The method of item 14, the loss function comprising a first component and a second component, wherein:

for each of the plurality of day types,

16. The method of any one of items 13 to 15, wherein for each of the plurality of day types, the determining a difference between the overall operation data and the corresponding overall historical operation data using a loss function comprises:

17. The method of item 16, the loss function comprising a third component and a fourth component, wherein:

for each of the plurality of day types,

18. The method of item 13, wherein the method further comprises:

obtaining temporal information of the target date;

obtaining, temporal information and day types of a plurality of third historical dates; and

19. The method of item 13, wherein the method further comprises:

determining that the target date is a rest day; and

in response to a determination that the target date is a rest day,

obtaining, temporal information of the target date; and

20. The method of any one of items 13 to 19, wherein the loss function is at least one of a linear loss function, an absolute loss function, a quadratic loss function, or a square root loss function.

21. The method of any one of items 13 to 20, wherein the day type of the target date is at least one of a working day, a rest day, a weekend, a holiday, or a festival.

22. The method of any one of items 13 to 21, wherein the determining an operation strategy with respect to the registered user terminal of the service platform based on the day type of the target date further comprises:

23. The method of any one of items 13 to 22, wherein the determining an operation strategy with respect to the registered user terminal of the service platform based on the day type of the target date further comprises:

24. The method of any one of items 13 to 23, wherein the loss function is determined according to a loss function determination process, the loss function determination process including:

obtaining a plurality of candidate loss functions; and

25. A system for determining a day type of a target date among a plurality of day types, comprising an obtaining module and a determination module, wherein:

the obtaining module is configured to:

obtain overall operation data of a service platform associated with the target date, the service platform configured to communicate, via the communication port, with at least one registered user terminal; and

for each of the plurality of day types, obtain overall historical operation data of the service platform associated with one or more first historical dates, the one or more first historical dates being of the day type and associated with the target date; and the determining module is configured to:

for each of the plurality of day types, determine a difference between the overall operation data and the corresponding overall historical operation data using a loss function, wherein an input to the loss function includes the overall operation data and the corresponding overall historical operation data;

determine, based on the differences corresponding to the plurality of day types, the day type of the target date; and

determine, based on the day type of the target date, an operation strategy with respect to the registered user terminal of the service platform.

26. A non-transitory computer-readable storage medium embodying a computer program product, the computer program product comprising instructions for determining a day type of a target date among a plurality of day types and configured to cause a computing device to:

obtain overall operation data of a service platform associated with the target date, the service platform configured to communicate, via a communication port, with at least one registered user terminal;

for each of the plurality of day types, obtain overall historical operation data of the service platform associated with one or more first historical dates, the one or more first historical dates being of the day type and associated with the target date;

27. A system for a determining a loss function used in identifying a day type of a date, comprising:

at least one storage medium including a set of instructions; and

at least one processor in communication the at least one storage medium, wherein when executing the instructions, the at least one processor is configured to direct the system to perform operations including:

obtaining a day type of a sample target date and overall sample operation data of a service platform associated with the sample target date;

for each of a plurality of day types, obtaining overall sample historical operation data of the service platform associated with one or more first sample historical dates, the one or more first sample historical dates being of the day type and associated with the sample target date;

obtaining a plurality of candidate loss functions; and

28. The system of item 27, wherein to select the loss function from the plurality of candidate loss functions, the at least one processor is further configured to direct the system to perform additional operations including:

for each of the plurality of candidate loss functions, determining a predicted day type of the sample target date using the candidate loss function based on the overall sample operation data and the overall sample historical operation data;

for each of the plurality of candidate loss functions, determining an accuracy score of the candidate loss function based at least in part on the predicted day type and the day type of the sample target date; and

designating, among the plurality of candidate loss functions, the candidate loss function having the highest accuracy score as the loss function.

29. The system of item 28, wherein for each of the plurality of candidate loss functions, to determine a predicted day type of the sample target date using the candidate loss function, the at least one processor is further configured to direct the system to perform additional operations including:

for each of the plurality of day types, determining a sample difference between the overall sample operation data and the corresponding overall sample historical operation data using the candidate loss function, wherein an input to the candidate loss function includes the overall sample operation data and the corresponding overall sample historical operation data; and

determining, based on the sample differences corresponding to the plurality of day types, the predicted day type of the sample target date.

30. The system of item 29, wherein:

the overall sample operation data includes a plurality of sets of sample operation data in a plurality of time periods during the sample target date, each of the plurality of sets of sample operation data corresponding to one of the plurality of time periods, and

for each of the plurality of day types, the corresponding overall sample historical operation data includes a plurality of sets of sample historical operation data in the plurality of time periods during the corresponding one or more first sample historical dates, each of the plurality of sets of sample historical operation data corresponding to one of the plurality of time periods.

31. The system of item 30, at least one candidate loss function including a first component and a second component, wherein:

for each of the plurality of day types,

the first component is configured to determine, for each of plurality of time periods, a first sample difference between the set of sample operation data in the time period and the corresponding set of sample historical operation data in the time period, and

the second component is configured to determine the sample difference between the overall sample operation data and the corresponding overall sample historical operation data based on the first sample differences corresponding to the plurality of time periods.

32. The system of item 29, wherein for each of the plurality of day types, to determine a sample difference between the overall sample operation data and the corresponding overall sample historical operation data using the candidate loss function, the at least one processor is further configured to direct the system to perform additional operations including:

obtaining one or more day types of one or more second sample historical dates associated with the sample target date;

determining, based on the one or more day types of the one or more second sample historical dates, an initial day type of the sample target date; and

for the day type, determining the sample difference between the overall sample operation data and the corresponding overall sample historical operation data using the candidate loss function, wherein an input of the candidate loss function includes the overall sample operation data, the corresponding overall sample historical operation data, and the initial day type of the sample target date.

33. A method for a determining a loss function used in identifying a day type of a date, comprising:

obtaining a plurality of candidate loss functions; and

34. The method of item 33, wherein the selecting the loss function from the plurality of candidate loss functions comprises:

35. The method of item 34, wherein for each of the plurality of candidate loss functions, the determining a predicted day type of the sample target date using the candidate loss function comprises:

36. The method of item 35, wherein:

37. The method of item 36, at least one candidate loss function including a first component and a second component, wherein:

for each of the plurality of day types,

38. The method of item 35, wherein for each of the plurality of day types, the determining a sample difference between the overall sample operation data and the corresponding overall sample historical operation data using the candidate loss function comprises:

39. A system for a determining a loss function used in identifying a day type of a date, comprising an obtaining module and a selection module, wherein:

the obtaining module is configured to:

obtain a day type of a sample target date and overall sample operation data of a service platform associated with the sample target date;

for each of a plurality of day types, obtain overall sample historical operation data of the service platform associated with one or more first sample historical dates, the one or more first sample historical dates being of the day type and associated with the sample target date; and

obtain a plurality of candidate loss functions; and

the selection module is configured to select, from the plurality of candidate loss functions, the loss function based at least in part on the overall sample operation data, the day type of the sample target date, and the overall sample historical operation data corresponding to the plurality of day types.

40. A non-transitory computer-readable storage medium embodying a computer program product, the computer program product comprising instructions configured to cause a computing device to:

for each of a plurality of day types, obtain overall sample historical operation data of the service platform associated with one or more first sample historical dates, the one or more first sample historical dates being of the day type and associated with the sample target date;

obtain a plurality of candidate loss functions; and

select, from the plurality of candidate loss functions, the loss function based at least in part on the overall sample operation data, the day type of the sample target date, and the overall sample historical operation data corresponding to the plurality of day types.

Claims

A method for information recommendation based on a date type of a target date, comprising:

constructing a date classification model using information and date types of a plurality of historical dates;

determining, based on the date classification model and information related to the target date, a day type of the target date; and

recommending information to a user according to the day type of the target date.
The method of claim 1, wherein the constructing a date classification model using information and date types of a plurality of historical dates comprises:

obtaining one or more preliminary loss functions; and

constructing the date classification model by training the one or more preliminary loss functions using the information and the date types of the plurality of historical dates.
The method of claim 1 or 2, wherein:

the information of the target date includes at least one of a date on the solar calendar, a date on the lunar calendar, or solar term information, and

the day type of the target date includes at least one of a working day or a rest day.
The method of claim 1, wherein the recommending information to a user according to the day type of the target date comprises:

obtaining a plurality of traffic monitoring strategies corresponding to a plurality of day types;

determining, among the plurality of traffic monitoring strategies, a traffic monitoring strategy corresponding to the day type of the target date; and

implementing the traffic monitoring strategy corresponding to the day type of the target date and recommending traffic monitoring information to the user.
The method of claim 1, wherein the recommending information to a user according to the day type of the target date comprises:

determining, based on historical consumption information of the user and the day type of the target date, a user behavior of the user on the target date; and

recommending, based on the user behavior of the user on the target date, the information to the user.
A system for information recommendation based on a date type of a target day, comprising:

a model construction module configured to construct a date classification model using information and date types of a plurality of historical dates;

a determination module configured to determine, based on the date classification model and information related to the target date, a day type of the target date; and

a recommendation module configured to recommend information to a user according to the day type of the target date.
The system of claim 6, wherein the model construction module is further configured to:

obtain one or more preliminary loss functions; and

construct the date classification model by training the one or more preliminary loss functions using the information and the date types of the plurality of historical dates.
The system of claim 6 or 7, wherein:

the information of the target date includes at least one of a date on the solar calendar, a date on the lunar calendar, or solar term information, and

the day type of the target date includes at least one of a working day or a rest day.
The system of claim 6, wherein the recommendation module is further configured to:

obtain a plurality of traffic monitoring strategies corresponding to a plurality of day types;

determine, among the plurality of traffic monitoring strategies, a traffic monitoring strategy corresponding to the day type of the target date; and

implement the traffic monitoring strategy corresponding to the day type of the target date and recommending traffic monitoring information to the user.
The system of claim 6, wherein the recommendation module is further configured to:

determine, based on historical consumption information of the user and the day type of the target date, a user behavior of the user on the target date; and

recommend, based on the user behavior of the user on the target date, the information to the user.
A system for information recommendation based on a date type of a target day, comprising:

at least one storage medium including a set of instructions; and

at least one processor in communication with the at least one storage medium, wherein when executing the instructions, the at least one processor is configured to direct the system to perform operations including:

constructing a date classification model using information and date types of a plurality of historical dates;

determining, based on the date classification model and information related to the target date, a day type of the target date; and

recommending information to a user according to the day type of the target date.
The system of claim 11, wherein to construct a date classification model using information and date types of a plurality of historical dates, the at least one processor is further configured to direct the system to perform additional operations including:

obtaining one or more preliminary loss functions; and

constructing the date classification model by training the one or more preliminary loss functions using the information and the date types of the plurality of historical dates.
The system of claim 11 or 12, wherein:

the information of the target date includes at least one of a date on the solar calendar, a date on the lunar calendar, or solar term information, and

the day type of the target date includes at least one of a working day or a rest day.
The system of claim 11, wherein to recommend information to a user according to the day type of the target date, the at least one processor is further configured to direct the system to perform additional operations including:

obtaining a plurality of traffic monitoring strategies corresponding to a plurality of day types;

determining, among the plurality of traffic monitoring strategies, a traffic monitoring strategy corresponding to the day type of the target date; and

implementing the traffic monitoring strategy corresponding to the day type of the target date and recommending traffic monitoring information to the user.
The system of claim 11, wherein to recommend information to a user according to the day type of the target date, the at least one processor is further configured to direct the system to perform additional operations including:

determining, based on historical consumption information of the user and the day type of the target date, a user behavior of the user on the target date; and

recommending, based on the user behavior of the user on the target date, the information to the user.
A non-transitory computer-readable storage medium embodying a computer program product, the computer program product comprising instructions and configured to cause a computing device to:

construct a date classification model using information and date types of a plurality of historical dates;

determine, based on the date classification model and information related to a target date, a day type of the target date; and

recommend information to a user according to the day type of the target date.
The non-transitory computer-readable storage medium of claim 16, wherein to construct a date classification model using information and date types of a plurality of historical dates, the computer program product is further configured to cause the computing device to:

obtain one or more preliminary loss functions; and

construct the date classification model by training the one or more preliminary loss functions using the information and the date types of the plurality of historical dates.
The non-transitory computer-readable storage medium of claim 16 or 17, wherein:

the information of the target date includes at least one of a date on the solar calendar, a date on the lunar calendar, or solar term information, and

the day type of the target date includes at least one of a working day or a rest day.
The non-transitory computer-readable storage medium of claim 16, wherein to recommend information to a user according to the day type of the target date, the computer program product is further configured to cause the computing device to:

obtain a plurality of traffic monitoring strategies corresponding to a plurality of day types;

determine, among the plurality of traffic monitoring strategies, a traffic monitoring strategy corresponding to the day type of the target date; and

implement the traffic monitoring strategy corresponding to the day type of the target date and recommending traffic monitoring information to the user.
The non-transitory computer-readable storage medium of claim 16, wherein to recommend information to a user according to the day type of the target date, the computer program product is further configured to cause the computing device to:

determine, based on historical consumption information of the user and the day type of the target date, a user behavior of the user on the target date; and

recommend, based on the user behavior of the user on the target date, the information to the user.