CN111260424A

CN111260424A - Information processing method and device

Info

Publication number: CN111260424A
Application number: CN201811457891.8A
Authority: CN
Inventors: 栾桂凯; 卓呈祥; 路劲
Original assignee: Beijing Didi Infinity Technology and Development Co Ltd
Current assignee: Beijing Didi Infinity Technology and Development Co Ltd
Priority date: 2018-11-30
Filing date: 2018-11-30
Publication date: 2020-06-09

Abstract

The application provides an information processing method, wherein the method comprises the following steps: acquiring historical service order information of a user side in a preset historical time period; determining the service order attribute and the service order quantity initiated by the user side in the preset historical time period according to the historical service order information; and determining preference information of the user side for issuing the service order in at least one service order attribute according to the service order attributes and the number of the service orders, so that service resources can be reasonably configured for the user side in advance, and the service efficiency is improved.

Description

Information processing method and device

Technical Field

The present application relates to the field of computer information technologies, and in particular, to an information processing method and apparatus.

Background

With the development of the internet and the mobile terminal, people can finish respective trips through the mobile terminal and the internet, and convenience is brought to the trips of people.

Due to the difference of living environment, occupation, habit and the like of people, everyone has respective taxi taking requirements. In the prior art, when a user has a travel demand, service resource scheduling is performed temporarily, so that travel service is provided for the user. In this case, since the travel demand of the user cannot be predicted in advance, service resources are often not allocated enough for some order types, and the user cannot travel or is inconvenient to travel.

Disclosure of Invention

In view of this, an object of the embodiments of the present application is to provide an information processing method and apparatus, which can determine preference information of a user initiating a service order under at least one service order attribute, and can reasonably configure service resources for the user in advance, thereby improving service efficiency. .

In a first aspect, an information processing method provided in an embodiment of the present application includes:

acquiring historical service order information of a user side in a preset historical time period;

determining the service order attribute and the service order quantity initiated by the user side in the preset historical time period according to the historical service order information;

and determining preference information of initiating the service order by the user side at least one service order attribute according to the service order attribute and the service order quantity.

In an embodiment, the historical service order is a travel order, and the service order attribute is used to represent a travel distance corresponding to the travel order.

In an embodiment, the determining, according to the historical service order information, the service order attribute and the service order quantity initiated by the user terminal within the preset historical time period includes:

determining at least one service order attribute initiated by the user side in each preset time interval of a plurality of preset time intervals and the number of service orders corresponding to each service order attribute according to the historical service order information;

the determining, according to the service order attributes and the number of service orders, preference information of initiating a service order by the user side at least one service order attribute includes:

determining the service order proportion corresponding to each service order attribute in each preset time interval according to at least one service order attribute initiated in each preset time interval and the service order quantity corresponding to each service order attribute;

determining the average service order occupation ratio of each service order attribute in each preset time interval according to the number of the preset time intervals and the service order occupation ratio corresponding to each service order attribute in each preset time interval;

and determining preference information of the user side for issuing the service order at least one service order attribute according to the average ratio of the service order of each service order attribute in each preset time interval, the ratio of the service order corresponding to each service order attribute in each preset time interval, the number of the plurality of preset time intervals, the number of the service orders corresponding to each service order attribute in each preset time interval, and the number of the time intervals covered by the service order initiated by the user side.

In one embodiment, the average ratio score of the service orders of any kind of service order attribute in each preset time interval satisfies the following formula:

wherein, pct_tThe service order occupation ratio corresponding to any service order attribute in the T-th preset time interval is shown, and T represents the number of the preset time intervals.

In an embodiment, the determining, according to the average ratio of each service order in each preset time interval according to each service order attribute, the ratio of each service order corresponding to each service order attribute in each preset time interval, the number of the plurality of preset time intervals, the number of each service order corresponding to each service order attribute in each preset time interval, and the number of time intervals covered by the service order initiated by the user end, preference information for initiating a service order by the user end at least one service order attribute includes:

determining preference stability of initiating the service order under each service order attribute according to the number of the preset time intervals and the number of the service orders corresponding to each service order attribute in each preset time interval;

and determining preference information of the user terminal for issuing the service order in at least one service order attribute according to preference stability of issuing the service order in each service order attribute, average service order occupation ratio of each service order attribute in each preset time interval, service order occupation ratio corresponding to each service order attribute, the number of the plurality of preset time intervals, the number of service orders corresponding to each service order attribute in each preset time interval and the number of time intervals covered by the service order issued by the user terminal.

In one embodiment, the preference stability score for initiating a service order is placed under any of the service order attributes_StableSatisfies the following formula:

wherein, cnt_tAnd the quantity of the service orders corresponding to each service order attribute in the T-th preset time interval is represented, and T represents the quantity of the preset time interval.

In one embodiment, the determining preference information of initiating a service order at the user terminal in at least one service order attribute includes:

determining the service order frequency of the user side for issuing the service order under the service order attribute according to the service order occupation ratio corresponding to each service order attribute, the number of time intervals covered by the service order initiated by the user side and the number of the preset time intervals;

and determining preference information of the service order issued by the user terminal at least one service order attribute according to the service order frequency of issuing the service order at the service order attribute, the preference stability of issuing the service order at each service order attribute, the average occupation ratio of the service order of each service order attribute in each preset time interval and the number of the time intervals covered by the service order issued by the user terminal.

In one embodiment, the frequency score of service orders placing service orders with any service order attribute_{Frequency of}Satisfies the following formula:

wherein, T_aliveIndicating the number of time intervals covered by the service order initiated by the user, pct_tThe service order proportion corresponding to each service order attribute in the tth preset time interval is shown as 1if (pct)_t>0.65) else0) indicates that the value is 1 when the service order occupation ratio corresponding to each service order attribute is greater than the preset threshold value in the T-th preset time interval, otherwise, the value is 0, and T indicates the number of the preset time intervals.

In one embodiment, the preference information includes a preference degree, and the preference degree Y of the user terminal for initiating the service order under any service order attribute satisfies the following formula:

Y＝score×score_stable×score_{Frequency of}；

Wherein, score represents the average ratio of the service orders of any kind of service order attributes in each preset time interval, score_StableScore representing the stability of preference for placing a service order under any of the attributes of the service order_{Frequency of}Indicating the frequency of service orders placed to initiate service orders at the service order attribute.

In one embodiment, the determining, according to the service order attribute and the service order quantity, preference information of initiating a service order by the user terminal at least one service order attribute includes:

aiming at any service order attribute, constructing a service order feature vector of a service order initiated under the service order attribute according to the service order quantity corresponding to the service order attribute in each preset time interval;

and inputting the service order feature vector into a pre-trained preference information detection model, and determining preference information of the service order initiated by the user side under any service attribute.

In one embodiment, the preference information detection model is trained by:

acquiring the quantity of service orders initiated by each sample user side in a plurality of preset time intervals and under different service attributes in each preset time interval of the plurality of sample user sides and actual preference information corresponding to the sample user side;

constructing a characteristic vector of the sample user side according to the quantity of service orders initiated by the sample user side under different service attributes in each preset time interval of a plurality of preset time intervals; inputting the characteristic vector into a basic detection model to obtain a preference information detection result of the sample user side;

and training the basic detection model according to the preference information detection result and the actual preference information to obtain the preference information detection model.

In an embodiment, the training the basic detection model according to the preference information detection result and the actual preference information to obtain the preference information detection model includes:

according to the preference information detection result of each sample user side and corresponding actual preference information, after one round of training is carried out on the basic detection model, the training parameters of the basic detection model are adjusted and the next round of training is carried out, and the basic detection model after multiple rounds of training is determined as the preference information detection model.

In one embodiment, each round of training of the base detection model is performed using the following steps:

determining any one sample user side in the sample user sides which have not completed training in the current round as a target sample user side, and determining the cross entropy loss of the target sample user side in the current round according to the preference information detection result of the target sample user side and the corresponding actual preference information;

adjusting the training parameters of the basic detection model according to the cross entropy loss of the target sample user side in the current round;

taking the target sample user side as a sample user side which completes training in the current round, and determining any one sample user side in the sample user sides which do not complete training in the current round as a new target sample user;

obtaining a preference information detection result of the new target sample user side by using the basic detection model with the adjusted parameters, and returning back the preference information detection result of the target sample user and corresponding actual preference information to determine the cross entropy loss of the target sample user side in the current round;

and completing the training of the current round of the basic detection model until all the sample user sides finish the training of the current round.

In a second aspect, an embodiment of the present application provides an information processing apparatus, including:

the acquisition module is used for acquiring historical service order information of the user terminal in a preset historical time period;

the quantity determining module is used for determining the service order attribute and the service order quantity initiated by the user side in the preset historical time period according to the historical service order information;

and the information determining module is used for determining preference information of the service order issued by the user side at least one service order attribute according to the service order attribute and the service order quantity.

In an embodiment, the quantity determining module is configured to determine the service order attribute and the service order quantity initiated by the user end within the preset historical time period by using the following method:

the information determining module is used for determining preference information of the user side for issuing the service order under at least one service order attribute by adopting the following modes:

In an embodiment, the information determining module is specifically configured to determine preference information of initiating a service order by the user side in at least one service order attribute by using the following method:

Y＝score×score_stable×score_{Frequency of}；

Wherein, score represents the average ratio of the service orders of any kind of service order attributes in each preset time interval, score_StableScore representing the stability of preference for placing a service order under any of the attributes of the service order_{Frequency of}Indicating the frequency of service orders initiating a service order under any service order attribute.

In an embodiment, the information obtaining module is further configured to determine preference information of initiating a service order at the user side in at least one service order attribute by using the following method:

In one embodiment, the apparatus further comprises a training module;

the training module is used for training to obtain the preference information detection model in the following way:

In an embodiment, the training module is specifically configured to train the basic detection model in the following manner:

In an embodiment, the training module is specifically configured to perform each round of training on the basic detection model by using the following steps:

In a third aspect, an embodiment of the present application provides an electronic device, including: a processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, the processor and the memory communicate via the bus when the electronic device is running, and the machine-readable instructions, when executed by the processor, perform the steps of the first aspect, or the information processing method described in any possible implementation manner of the first aspect.

In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and the computer program is executed by a processor to perform the steps of the first aspect, or the information processing method described in any possible implementation manner of the first aspect.

In the information processing method and apparatus provided by the embodiment of the application, historical service order information of a user terminal in a preset historical time period is obtained, then, according to the obtained historical service order information, a service order attribute and a service order quantity initiated by the user terminal in the preset historical time period can be obtained, and according to the service order attribute and the service order quantity, preference information of the user terminal for initiating a service order in at least one service order attribute is obtained. Based on the preference information, the resource configuration can be optimized, and the service efficiency is improved. For example, through the predicted travel demand of the user for a specific service order type, service resources (such as vehicles) can be reasonably configured in advance for the user side, and the service efficiency is improved.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.

Fig. 1 shows a system 100 structure diagram of an application scenario provided in an embodiment of the present application;

FIG. 2 is a flow chart illustrating an information processing method provided by an embodiment of the present application;

fig. 3 is a flowchart illustrating a specific method for determining preference information of a user initiating a service order under at least one service order attribute in an information processing method provided in an embodiment of the present application;

fig. 4 is a flowchart illustrating another specific method for determining preference information of initiating a service order at the user side in at least one service order attribute in the information processing method according to the embodiment of the present application;

fig. 5 is a flowchart illustrating a specific method for training a preference information detection model in an information processing method provided in an embodiment of the present application;

fig. 6 is a schematic structural diagram illustrating an information processing apparatus according to an embodiment of the present application;

fig. 7 shows a schematic structural diagram of an electronic device provided in an embodiment of the present application.

Detailed Description

In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it should be understood that the drawings in the present application are for illustrative and descriptive purposes only and are not used to limit the scope of protection of the present application. Additionally, it should be understood that the schematic drawings are not necessarily drawn to scale. The flowcharts used in this application illustrate operations implemented according to some embodiments of the present application. It should be understood that the operations of the flow diagrams may be performed out of order, and steps without logical context may be performed in reverse order or simultaneously. One skilled in the art, under the guidance of this application, may add one or more other operations to, or remove one or more operations from, the flowchart.

In addition, the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without making any creative effort, shall fall within the protection scope of the present application.

The method or the device described below in the embodiments of the present application can be applied to any scene that needs to generate preference information, for example, can be applied to mobile phone application software, a web page design platform, and the like. The embodiment of the present application does not limit a specific application scenario, and any scheme for generating preference information by using the method provided by the embodiment of the present application is within the protection scope of the present application.

It should be noted that in the embodiments of the present application, the term "comprising" is used to indicate the presence of the features stated hereinafter, but does not exclude the addition of further features.

The term "user side" in this application may refer to an individual, entity or tool that requests a service, subscribes to a service, provides a service, or facilitates the provision of a service. For example, the user side may be a passenger, a driver, an operator, etc., or any combination thereof.

The terms "service order" and "service request" are used interchangeably herein to refer to an order initiated by a passenger, a service requester, a driver, a service provider, a supplier, or the like, or any combination thereof. Accepting the "service order" or "request" may be a passenger, a service requester, a driver, a service provider, a supplier, or the like, or any combination thereof. The service order may be charged or free.

In the embodiment of the application, historical service order information of a user terminal in a preset historical time period is obtained, then the service order attribute and the service order quantity initiated by the user terminal in the preset historical time period can be obtained according to the obtained historical service order information, and the preference information of the user terminal for initiating the service order in at least one service order attribute is obtained according to the service order attribute and the service order quantity, so that on one hand, when preference resource information of some travel services is provided for the user, preference resources can be provided for the user in a targeted manner according to predicted preference information of the user for specific service order attributes (such as long-distance orders), and the resources are effectively and reasonably utilized; on the other hand, through the predicted travel demand of the user for the specific service order type, service resources (such as vehicles) can be reasonably configured for the user side in advance, and the service efficiency is improved.

Fig. 1 is a system 100 structure diagram of an application scenario according to an embodiment of the present application. For example, the system 100 may be an online transportation service platform for transportation services such as taxi cab, designated drive service, express, carpool, bus service, driver rental, or regular service, or any combination thereof. System 100 may include one or more of a server 110, a network 120, a client 130, and a database 140, and server 110 may include a processor that performs operations on instructions.

In some embodiments, the server 110 may be a single server or a group of servers. The set of servers can be centralized or distributed (e.g., the servers 110 can be a distributed system). In some embodiments, the server 110 may be local or remote to the terminal. For example, server 110 may access information and/or data stored in user terminal 130, or database 140, or any combination thereof, via network 120. As another example, server 110 may be directly connected to at least one of user terminal 130 and database 140 to access stored information and/or data. In some embodiments, the server 110 may be implemented on a cloud platform; by way of example only, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud (community cloud), a distributed cloud, an inter-cloud, a multi-cloud, and the like, or any combination thereof. In some embodiments, the server 110 may be implemented on an electronic device having one or more components.

In some embodiments, a processor may include one or more processing cores (e.g., a single-core processor or a multi-core processor). Merely by way of example, a Processor 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 Physical 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 (Reduced Instruction Set computer), a microprocessor, or the like, or any combination thereof.

Network 120 may be used for the exchange of information and/or data. In some embodiments, one or more components in system 100 (e.g., server 110, client 130, and database 140) may send information and/or data to other components. For example, the server 110 may obtain a service request from the user terminal 130 via the network 120. In some embodiments, the network 120 may be any type of wired or wireless network, or combination thereof. In some embodiments, the user of the user end 130 may be a person other than the actual demander of the service. For example, the user a of the user terminal 130 may use the user terminal 130 to initiate a service request for the service actual demander B (for example, the user a may call a car for his friend B), or receive service information or instructions from the server 110.

In some embodiments, the user terminal 130 may include a mobile device, a tablet computer, a laptop computer, or a built-in device in a motor vehicle, etc., or any combination thereof. In some embodiments, the mobile device may include a smart home device, a wearable 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 devices may include smart lighting devices, control devices for smart electrical devices, smart monitoring devices, smart televisions, smart cameras, or walkie-talkies, or the like, or any combination thereof. In some embodiments, the wearable device may include a smart bracelet, a smart lace, smart glass, a smart helmet, a smart watch, a smart garment, a smart backpack, a smart accessory, and 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, or 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 glass, a virtual reality patch, an augmented reality helmet, augmented reality glass, an augmented reality patch, or the like, or any combination thereof. For example, the virtual reality device and/or augmented reality device may include various virtual reality products and the like. In some embodiments, the built-in devices in the motor vehicle may include an on-board computer, an on-board television, and the like. In some embodiments, the user terminal 130 may be a device having a positioning technology for locating the location of the service requester and/or the user terminal.

Database 140 may store data and/or instructions. In some embodiments, database 140 may store data obtained and/or obtained from user terminals 130. In some embodiments, database 140 may store data and/or instructions for the exemplary methods described herein. In some embodiments, the database 140 may include mass storage, removable storage, volatile Read-write Memory, or Read-Only Memory (ROM), among others, or any combination thereof. By way of example, mass storage may include magnetic disks, optical disks, solid state drives, and the like; removable memory may include flash drives, floppy disks, optical disks, memory cards, zip disks, tapes, and the like; volatile read-write Memory may include Random Access Memory (RAM); the RAM may include Dynamic RAM (DRAM), Double data Rate Synchronous Dynamic RAM (DDR SDRAM); static RAM (SRAM), Thyristor-Based Random Access Memory (T-RAM), Zero-capacitor RAM (Zero-RAM), and the like. By way of example, ROMs may include Mask Read-Only memories (MROMs), Programmable ROMs (PROMs), Erasable Programmable ROMs (PERROMs), Electrically Erasable Programmable ROMs (EEPROMs), compact disk ROMs (CD-ROMs), digital versatile disks (ROMs), and the like. In some embodiments, database 140 may be implemented on a cloud platform. By way of example only, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, across clouds, multiple clouds, or the like, or any combination thereof.

In some embodiments, a database 140 may be connected to network 120 to communicate with one or more components in system 100 (e.g., server 110, client 130, etc.). One or more components in system 100 may access data or instructions stored in database 140 via network 120. In some embodiments, the database 140 may be directly connected to one or more components in the system 100 (e.g., the server 110, the client 130, etc.); alternatively, in some embodiments, database 140 may also be part of server 110.

In some embodiments, one or more components in system 100 (e.g., server 110, client 130, etc.) may have access to database 140.

The following embodiment will explain the information processing procedure in detail. The following information processing method may be implemented in the server 110, and specifically, the processor in the server 110 may execute the relevant method instructions.

Referring to fig. 2, a basic flow of an information processing method provided in an embodiment of the present application includes:

s201: acquiring historical service order information of a user terminal in a preset historical time period.

In a specific implementation, the preset historical time period may be a time length from a certain time point of the history to a time point of acquiring the historical service order information of the user terminal, for example, the historical service order information of the user terminal needs to be acquired in 3/9 th in 2018, and if the preset historical time period is one year, the acquired historical service order information is from 3/9 th in 2017 to 3/9 th in 2018; the preset historical time period may also be a time length with any time as a starting point or an ending point, for example, the preset historical time period is one year, historical service order information of the user terminal needs to be acquired in 3/9/2018, and the acquired historical service order information is from 1/9/2017 to 1/9/2018.

In some embodiments, the server may obtain the historical service order information of the user terminal in the preset historical time period in the database, for example, store data of each time the user terminal initiates a service order as the historical service order information in the database, and when the server needs to obtain the historical service order information of the user terminal, the server may retrieve the historical service order information from the database. The historical service order information may include service order content, user information, time for initiating a service order, service time corresponding to the order, and the like, for example, if the service order is a travel order, the historical service order information may include travel time, a travel location, a travel distance, and the like, and the travel location may include a travel starting point and a travel ending point.

Here, when obtaining the historical service order information of the user terminal, the corresponding historical service order information may be obtained based on the user account registered by the user terminal.

S202: and determining the service order attribute and the service order quantity initiated by the user terminal in the preset historical time period according to the historical service order information.

In a specific implementation, the historical service order may be a travel order, and the service order attributes may include a long-distance order and a short-distance order, and may further include a long-distance order, a short-distance order, a medium-distance order, and the like, for example: the travel distance of the travel order is within 10 kilometers, the service order attribute of the travel order at the moment is the short-distance order, the travel distance of the travel order is the medium-distance order within 10 kilometers to 30 kilometers, the service order attribute of the travel order at the moment is the medium-distance order, the travel distance of the travel order is the long-distance order above 30 kilometers, and the service order attribute of the travel order is the long-distance order.

After obtaining historical service order information in a preset historical time period, determining the service order attribute of each historical service order according to the trip distance in the historical service order information and the distance range corresponding to each preset service order attribute, and determining the number of service orders according to the historical service order information, wherein when determining the number of service orders, not only determining the total number of service orders, but also determining the number of service orders initiated under each service order attribute, for example, when the preset historical time period is one year, obtaining historical service order information as travel orders corresponding to service orders initiated by the user terminal a from 11.1.2017.11.1 to 11.1.2018.11.1, obtaining the total number of travel orders of the user terminal a in one year as 126 according to the information such as the trip distance and the trip time corresponding to the travel orders of the user terminal a, the number of travel orders with the service order attribute of long-distance orders is 84, the number of travel orders with the service order attribute of medium-distance orders is 7, and the number of travel orders with the service order attribute of short-distance orders is 35.

In some embodiments, determining, according to the historical service order information, an attribute and a quantity of service orders initiated by the user terminal within a preset historical time period further includes: and determining at least one service order attribute initiated by the user terminal in each preset time interval in the plurality of preset time intervals and the number of service orders corresponding to each service order attribute according to the historical service order information.

In a specific implementation, the preset time interval refers to a time interval obtained by dividing a preset historical time period according to a certain time length, for example, the preset historical time period is a whole year from 1 month and 1 day in 2018 to 12 months and 31 days in 2018, and the preset time interval may be one month, one quarter or 15 days. According to the historical service order information, at least one service order attribute initiated by the user terminal in each preset time interval in the preset time intervals in the preset historical time period and the service order quantity corresponding to each service order attribute can be determined.

S203: and determining preference information of initiating the service order by the user side at least one service order attribute according to the service order attribute and the service order quantity.

In a specific implementation, the preference information is used to reflect a service order attribute of a service order that the user terminal prefers to initiate, and may be a probability value or character information indicating whether such a service order attribute is preferred. According to the service order attribute and the service order quantity initiated by the user side, the preference information of initiating the service order by the user side at least one service order attribute can be determined. According to the obtained preference information of the user side, the corresponding service resources are matched for the user side, for example, when the service order is a travel order, the preference resources corresponding to the preference information can be pushed to the user side, for example, order discount information, deduction information and the like are pushed for a long-distance order. In addition, according to the service order attribute preferred by the user side, the corresponding service resources can be matched for the user side in advance, for example, the service resources such as vehicles and the like are prepared for the user in advance, so that the situation that the user cannot go out or is inconvenient to go out is avoided.

In some embodiments, step S203 comprises: determining the service order proportion corresponding to each service order attribute in each preset time interval according to at least one service order attribute initiated in each preset time interval and the service order quantity corresponding to each service order attribute;

In specific implementation, according to at least one service order attribute in each preset time interval and the service order quantity corresponding to each service order attribute, the service order proportion corresponding to each service order attribute in each preset time interval of the user side can be determined. In addition, when the preset historical time period is divided into the preset time intervals, the number of the divided preset time intervals also needs to be acquired, and according to the number of the preset time intervals and the service order proportion corresponding to each service order attribute in each preset time interval, the service order average proportion score of each service order attribute in each preset time interval at the user side can be acquired, wherein the service order average proportion score of any service order attribute in each preset time interval meets the following formula:

After the average occupation ratio of the service orders is determined, the preference information of the user side for issuing the service orders at least one service order attribute is determined according to the average occupation ratio of the service orders of each service order attribute in each preset time interval, the service order occupation ratio corresponding to each service order attribute, the number of a plurality of preset time intervals, the number of the service orders corresponding to each service order attribute in each preset time interval and the number of the time intervals covered by the service orders initiated by the user side in each preset time interval.

Specifically, according to the number of the plurality of preset time intervals and the number of the service orders corresponding to each service order attribute in each preset time interval, the preference stability of initiating the service orders under each service order attribute can be obtained, and the preference stability can represent the stable state of the service orders initiating any service order attribute, wherein the preference stability score of initiating the service orders under any service order attribute_StableSatisfies the following formula:

After determining the preference stability of the user terminal for initiating the service order under each service order attribute, determining the preference information of the user terminal for initiating the service order under at least one service order attribute according to the preference stability of the user terminal for initiating the service order under each service order attribute, the average occupation ratio of the service order of each service order attribute in each preset time interval, the occupation ratio of the service order corresponding to each service order attribute, the number of a plurality of preset time intervals, the number of the service orders corresponding to each service order attribute in each preset time interval and the number of the time intervals covered by the service order initiated by the user terminal.

Specifically, referring to fig. 3, a flowchart of a specific method for determining preference information of a user initiating a service order under at least one service order attribute is provided for the embodiment of the present application, and includes:

s301: and determining the service order frequency of the user side for issuing the service order under the service order attribute according to the service order occupation ratio corresponding to each service order attribute, the number of time intervals covered by the service order initiated by the user side and the number of the preset time intervals.

In specific implementation, according to the service order proportion corresponding to each service order attribute, the number of time intervals covered by the service order initiated by the user terminal and the number of a plurality of preset time intervals, the service order frequency of initiating the service order by the service order attribute of the user terminal can be obtained, the service order average frequency can measure the frequency of initiating the travel order of each service order attribute of the user terminal, wherein the service order frequency score can measure the frequency of initiating the travel order of each service order attribute of the user terminal_{Frequency of}Satisfies the following formula:

S302: and determining preference information of the user terminal for issuing the service order under at least one service order attribute according to the frequency of the service order issued under the service order attribute, the preference stability of the service order issued under each service order attribute, the average occupation ratio of the service order of each service order attribute in each preset time interval and the number of the time intervals covered by the service order issued by the user terminal.

In a specific implementation, when determining preference information of initiating a service order under a service order attribute, it is necessary to determine a frequency of initiating the service order under the service order attribute, a preference stability of initiating the service order under the service order attribute, an average ratio of the service orders under the service order attribute in each preset time interval, and a number of time intervals covered by initiating the service order by the user terminal within a preset historical time period.

In some embodiments, the preference information includes a preference degree, the preference degree is used to indicate a preference degree of the user terminal for issuing a service order under any service order attribute, and the preference degree Y satisfies the following formula, after determining a frequency of service orders issued under any service order attribute of the user terminal, a preference stability of service orders issued by the service order attribute, an average percentage of service orders in each preset time interval under the service order attribute, and a number of time intervals covered by service orders issued by the user terminal within a preset historical time period, the preference degree of service orders issued by the service order attribute is calculated:

Y＝score×score_stable×score_{Frequency of}；

Referring to fig. 4, another embodiment of the present application further provides another specific method for determining, according to the service order attribute and the service order quantity, preference information of initiating a service order by the user side at least one service order attribute, including:

s401: and aiming at any service order attribute, constructing a service order feature vector of the service order initiated by the service order attribute according to the service order quantity corresponding to the service order attribute in each preset time interval.

In specific implementation, for each service order attribute, the service order quantity corresponding to the service order attribute in each preset time interval of the user side is used for constructing a service order feature vector of a service order initiated under the service order attribute, for example, if the service order attribute is a long-distance service order, the preset historical time period is 6 months in 2017 to 12 months in 2017, the preset time interval is one month, the singular quantity of the long-distance service order initiated by the user side in each preset time interval is 3, 3, 5, 6, 4, 2, respectively, and the service order feature vector is [3, 3, 5, 6, 4, 2 ].

It should be noted that the service order attributes in the embodiment of the present application only include two types, a long-distance service order and an extra-long-distance service order, where the long-distance service order and the non-long-distance service order can be determined by a preset distance threshold, for example, a long-distance service order is determined if the user terminal has a travel distance greater than 30 km, and a non-long-distance service order is determined if the user terminal has a travel distance less than or equal to 30 km.

S402: and inputting the service order feature vector into a pre-trained preference information detection model, and determining preference information of the service order initiated by the user side under any service attribute.

In a specific implementation, the constructed feature vector of the service order is input into the pre-trained preference information detection model, so as to determine the preference information of the user terminal for issuing the service order at any service order attribute, for example, if the feature vector of the service order corresponding to the long-distance service order initiated by the user terminal is [3, 3, 5, 6, 4, 2], the feature vector is input into the pre-trained preference information detection model, so that the preference information of the user terminal for initiating the long-distance service order can be obtained.

Specifically, referring to fig. 5, an embodiment of the present application further provides a specific method for training a preference information detection model, including:

s501: the method comprises the steps of obtaining the quantity of service orders initiated by each sample user side in a plurality of preset time intervals and under different service attributes in each preset time interval of the plurality of sample user sides, and obtaining actual preference information corresponding to the sample user side.

In an implementation, the sample user side includes a positive sample user side and a negative sample user side, for example, when the service order attribute includes a long-distance service order and a non-long-distance service order, the preset historical time period is one year, the positive sample user side may be configured such that the number of long-distance service orders initiated by the sample user side accounts for 98% of the total number of initiated service orders in the year, and the number of non-long-distance service orders initiated accounts for 2% of the total number of initiated service orders as the positive sample user side. The negative sample client may be that the sample client initiates long-distance service orders in a number of 2% of the total number of initiated service orders and initiates non-long-distance service orders in a number of 98% of the total number of initiated service orders in the year.

After the sample user sides are determined, the number of service orders with each service order attribute is determined to be respectively initiated by each sample user side in each preset time interval according to the historical service order information of the sample user sides, and the actual preference information corresponding to each sample user side is obtained, wherein the actual preference information can be a label or a numerical value, for example, the actual preference information of the positive sample user side can be 1, and the actual preference information of the negative sample user side can be 0.

S502: constructing a characteristic vector of the sample user side according to the quantity of service orders initiated by the sample user side under different service attributes in each preset time interval of a plurality of preset time intervals; and inputting the characteristic vector into a basic detection model to obtain a preference information detection result of the sample user side.

When constructing the feature vector of the sample user side, the step S401 is described in detail as the step S401.

In some embodiments, the underlying detection model may be comprised of a neural network and a classifier, such as a recurrent neural network. The neural network comprises a plurality of layers of feature extraction layers, the plurality of layers of feature extraction layers can extract features of the constructed measured feature vectors, and the results after feature extraction are input into the classifier to obtain preference information detection results.

S503: and training the basic detection model according to the preference information detection result and the actual preference information to obtain the preference information detection model.

In the specific implementation, after the preference information detection result is obtained, the basic detection model is trained according to the preference information detection result and the actual preference information, and in the training process, parameters of the basic detection model are adjusted according to the preference information detection result and the actual preference information, so that the preference information detection model is obtained, and the basic detection model is trained for multiple times.

In some embodiments, during each round of training of the basic detection model, one sample user side of the round of sample user sides which have not been trained is used as a target user side, cross entropy loss between the round of preference information detection result and the actual preference information of the target sample user side can be determined according to the preference information detection result and the actual preference information of the sample user side, training parameters of the basic detection model are adjusted according to the cross entropy loss of the sample user side in the round, the target sample user side is used as the round of sample user side which has been trained, any sample user side of the round of sample user sides which have not been trained is determined as a new target sample user, the parameter-adjusted basic detection model is used to obtain the preference information detection result of the new target sample user side, and the cross entropy loss between the preference information detection result of the new target sample user and the corresponding actual preference information is calculated And repeating the steps until all the sample user terminals finish the training of the current round, and finishing the training of the current round of the basic detection model.

In the information processing method provided by the embodiment of the application, historical service order information of a user terminal in a preset historical time period is obtained, then, according to the obtained historical service order information, a service order attribute and a service order quantity initiated by the user terminal in the preset historical time period can be obtained, and according to the service order attribute and the service order quantity, preference information of the user terminal for initiating a service order in at least one service order attribute is obtained. Compared with the problem of inaccurate service resource configuration in the prior art, the method and the device for configuring the service resources can determine the preference information of the service order issued by the user side at least one service order attribute, and further perform service resource configuration on the user in a more targeted manner according to the preference information of the user, so that the utilization rate of the service resources is improved.

Based on the above information processing method, referring to fig. 6, an embodiment of the present application further provides an information processing apparatus 600, including: an acquisition module 610, a quantity determination module 620, and an information determination module 630; wherein the content of the first and second substances,

the acquiring module 610 is configured to acquire historical service order information of a user terminal within a preset historical time period;

a quantity determining module 620, configured to determine, according to the historical service order information, a service order attribute and a service order quantity initiated by the user within the preset historical time period;

an information determining module 630, configured to determine, according to the service order attribute and the number of service orders, preference information for initiating a service order by the user side in at least one service order attribute.

In some embodiments, the historical service order is a travel order, and the service order attribute is used to represent a travel distance corresponding to the travel order.

In some embodiments, the quantity determining module 620 is configured to determine the service order attribute and the service order quantity initiated by the user end within the preset historical time period by:

the information determining module 630 is configured to determine preference information of initiating a service order by the user side according to at least one service order attribute by using the following method:

In some embodiments, the average service order proportion score of any service order attribute at each preset time interval satisfies the following formula:

In some embodiments, the information determining module 630 is specifically configured to determine the preference information of the user side for initiating the service order in at least one service order attribute by using the following method:

In some embodiments, the preference stability score for initiating a service order is placed under either service order attribute_StableSatisfies the following formula:

In some embodiments, the information determining module 630 is specifically configured to determine the preference information of the user side for placing the service order in at least one service order attribute by using the following method:

In some embodiments, the frequency score of service orders placing service orders with any service order attribute_{Frequency of}Satisfies the following formula:

In some embodiments, the preference information includes a preference, and the preference Y of the user terminal for placing a service order under any service order attribute satisfies the following formula:

Y＝score×score_stable×score_{Frequency of}；

In some embodiments, the information obtaining module 630 is further configured to determine the preference information of the user terminal for initiating the service order in at least one service order attribute by using the following method:

In some embodiments, the apparatus further comprises a training module 640;

the training module 640 is configured to train to obtain the preference information detection model in the following manner:

In some embodiments, the training module 640 is specifically configured to train the basic detection model in the following manner:

In some embodiments, the training module 640 is specifically configured to perform each round of training on the basic detection model by using the following steps:

The modules may be connected or in communication with each other via a wired or wireless connection. The wired connection may include a metal cable, an optical cable, a hybrid cable, etc., or any combination thereof. The wireless connection may comprise a connection over a LAN, WAN, bluetooth, ZigBee, NFC, or the like, or any combination thereof. Two or more modules may be combined into a single module, and any one module may be divided into two or more units.

Referring to fig. 7, embodiments of the present application further provide a schematic diagram of exemplary hardware and software components of an electronic device 700 that may implement the concepts of the present application. A processor 720 may be used on the electronic device 700 and to perform the functions described herein.

The electronic device 700 may be a general-purpose computer or a special-purpose computer, both of which may be used to implement the information pushing method of the present application. Although only a single computer is shown, for convenience, the functions described herein may be implemented in a distributed fashion across multiple similar platforms to balance processing loads.

For example, electronic device 700 may include a network port 710 connected to a network, one or more processors 720 for executing program instructions, a communication bus 730, and a different form of storage medium 740, such as a disk, ROM, or RAM, or any combination thereof. Illustratively, the computer platform may also include program instructions stored in ROM, RAM, or other types of non-transitory storage media, or any combination thereof. The method of the present application may be implemented in accordance with these program instructions. The electronic device 700 also includes an Input/Output (I/O) interface 750 between the computer and other Input/Output devices (e.g., keyboard, display screen).

For ease of illustration, only one processor is depicted in the electronic device 700. However, it should be noted that the electronic device 700 in the present application may also comprise multiple processors, and thus the steps performed by one processor described in the present application may also be performed by multiple processors in combination or individually. For example, if the processor of the electronic device 700 performs step a and step B, it should be understood that step a and step B may also be performed by two different processors together or performed separately in one processor. For example, a first processor performs step a and a second processor performs step B, or the first processor and the second processor perform steps a and B together.

In specific implementation, the storage medium 740 stores machine-readable instructions executable by the processor 720, when the electronic device runs, the processor 720 communicates with the storage medium 740 through the communication bus 730, and the machine-readable instructions are executed by the processor 720 to perform the information processing method, so that the problem that a user cannot go out or is inconvenient to go out due to insufficient allocation of service resources in the prior art is solved, and the effects of reasonably configuring service resources for a user side in advance and improving service efficiency are achieved.

The embodiment of the application also provides a computer readable storage medium, wherein a computer program is stored on the computer readable storage medium, and when the computer program is executed by a processor, the steps of the information processing method are executed.

Specifically, the storage medium can be a general storage medium, such as a mobile disk, a hard disk, and the like, and when a computer program on the storage medium is executed, the information processing method can be executed, so that the problem that a user cannot go out or is inconvenient to go out due to insufficient allocation of service resources in the prior art is solved, and the effects of reasonably allocating the service resources in advance for a user side and improving service efficiency are achieved.

The computer program product of the information processing method and apparatus provided in the embodiments of the present application includes a computer-readable storage medium storing a program code, where instructions included in the program code may be used to execute the method described in the foregoing method embodiments, and specific implementation may refer to the method embodiments, and will not be described herein again.

It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the system and the apparatus described above may refer to corresponding processes in the method embodiments, and are not described in detail in this application. In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. The above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is merely a logical division, and there may be other divisions in actual implementation, and for example, a plurality of modules or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or modules through some communication interfaces, and may be in an electrical, mechanical or other form.

The modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.

The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a non-volatile computer-readable storage medium executable by a processor. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a U disk, a removable hard disk, a ROM, a RAM, a magnetic disk, or an optical disk.

The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. An information processing method characterized by comprising:

2. The method of claim 1, wherein the historical service order is a travel order, and the service order attribute is used for representing a travel distance corresponding to the travel order.

3. The method according to claim 1, wherein the determining, according to the historical service order information, the service order attribute and the service order quantity initiated by the user terminal within the preset historical time period comprises:

4. The method of claim 3, wherein the average service order proportion score for any service order attribute at each predetermined time interval satisfies the following formula:

5. The method according to claim 4, wherein the determining the preference information of the user terminal for issuing the service order at the at least one service order attribute according to the average ratio of the service orders of each service order attribute in each preset time interval, the ratio of the service orders corresponding to each service order attribute in each preset time interval, the number of the plurality of preset time intervals, the number of the service orders corresponding to each service order attribute in each preset time interval, and the number of the time intervals covered by the service order initiated by the user terminal comprises:

6. The method of claim 5, wherein the preference stability score for initiating a service order is placed under any service order attribute_StableSatisfy the requirement ofThe following formula:

7. The method of claim 5, wherein the determining the preference information of the user terminal for initiating the service order in at least one service order attribute comprises:

8. The method of claim 7, wherein the service order frequency score for placing a service order with any service order attribute_{Frequency of}Satisfies the following formula:

wherein, T_aliveIndicating the number of time intervals covered by the service order initiated by the user, pct_tShowing the service order ratio corresponding to each service order attribute in the t-th preset time interval, 1if(pct_t>0.65) else0) indicates that the value is 1 when the service order occupation ratio corresponding to each service order attribute is greater than the preset threshold value in the T-th preset time interval, otherwise, the value is 0, and T indicates the number of the preset time intervals.

9. The method of claim 7, wherein the preference information comprises a preference degree, and the preference degree Y of the user terminal for placing the service order under any service order attribute satisfies the following formula:

Y＝score×score_stable×score_{Frequency of}；

10. The method of claim 3, wherein the determining the preference information of the user terminal for initiating the service order in at least one service order attribute according to the service order attribute and the service order quantity comprises:

11. The method of claim 10, wherein the preference information detection model is trained by:

12. The method of claim 11, wherein the training the basic detection model according to the preference information detection result and the actual preference information to obtain the preference information detection model comprises:

13. The method of claim 12, wherein each round of training of the base detection model is performed by:

14. An information processing apparatus characterized by comprising:

15. The apparatus of claim 14, wherein the historical service order is a travel order, and the service order attribute is used for representing a travel distance corresponding to the travel order.

16. The apparatus of claim 15, wherein the quantity determining module is configured to determine the service order attribute and the quantity of service orders initiated by the user terminal within the preset historical time period by:

17. The apparatus of claim 16, wherein the average service order proportion score of any service order attribute at each preset time interval satisfies the following formula:

18. The apparatus of claim 16, wherein the information determining module is specifically configured to determine the preference information of the user terminal for placing the service order under the at least one service order attribute by using the following method, and the method includes:

19. The apparatus of claim 18, wherein a preference stability score for initiating a service order under any service order attribute_StableSatisfies the following formula:

20. The apparatus of claim 18, wherein the information determining module is specifically configured to determine the preference information of the user side for placing the service order under the at least one service order attribute by:

21. The apparatus of claim 20, wherein the service order frequency score for placing a service order with any service order attribute_{Frequency of}Satisfies the following formula:

22. The apparatus of claim 20, wherein the preference information comprises a preference degree, and wherein the preference degree Y of the user terminal for placing the service order under any service order attribute satisfies the following formula:

Y＝score×score_stable×score_{Frequency of}；

Wherein, score represents the average ratio of the service orders of any kind of service order attributes in each preset time interval, score_StableScore representing the stability of preference for placing a service order under any of the attributes of the service order_{Frequency of}Indicating attributes of the service orderThe frequency of placing service orders from which service orders are initiated.

23. The apparatus of claim 16, wherein the information obtaining module is further configured to determine the preference information of the user terminal for placing the service order in the at least one service order attribute by:

24. The apparatus of claim 23, further comprising a training module;

25. The apparatus of claim 24, wherein the training module is specifically configured to:

26. The apparatus of claim 25, wherein the training module is specifically configured to perform each round of training on the basic detection model by:

27. An electronic device, comprising: processor, memory and bus, the memory storing machine readable instructions executable by the processor, the processor and the memory communicating via the bus when the electronic device is operating, the machine readable instructions when executed by the processor performing the steps of the information processing method according to any one of claims 1 to 13.

28. A computer-readable storage medium, characterized in that a computer program is stored thereon, which, when being executed by a processor, performs the steps of the information processing method according to any one of claims 1 to 13.