CN112801324A

CN112801324A - Travel recommendation method and device, electronic equipment and computer-readable storage medium

Info

Publication number: CN112801324A
Application number: CN202011619713.8A
Authority: CN
Inventors: 缪莹莹; 杨育聪; 董越
Original assignee: Beijing Didi Infinity Technology and Development Co Ltd
Current assignee: Beijing Didi Infinity Technology and Development Co Ltd
Priority date: 2020-12-31
Filing date: 2020-12-31
Publication date: 2021-05-14

Abstract

The application provides a travel recommendation method, a travel recommendation device, an electronic device and a computer-readable storage medium, wherein the method comprises the following steps: acquiring travel scene information of a position where a service requester places a travel order and supply and demand conditions of each travel service; determining the acceptance probability of the service requester to each travel service according to the travel scene information; and selecting a target travel service recommended to the service requester from the plurality of travel services according to the acceptance probability of the service requester to each travel service and the supply and demand conditions of each travel service. According to the method and the device, the influence of the travel scene information on the receiving probability of each travel service by the service requester and the supply and demand conditions of each travel service are considered, and the target travel service with the receiving probability and the supply and demand conditions both meeting the travel demand of the service requester recommended by the service requester is recommended to the service requester, so that the recommendation accuracy of the travel service can be improved.

Description

Travel recommendation method and device, electronic equipment and computer-readable storage medium

Technical Field

The present application relates to the field of information technologies, and in particular, to a travel recommendation method and apparatus, an electronic device, and a computer-readable storage medium.

Background

With the development of intelligent equipment and mobile internet technology, travel service software brings great convenience to people's travel. Currently, the use of network travel services is a common requirement for people in all levels of society.

At present, various optional travel services are available in conventional travel, and the travel services can meet the travel demands of people in different aspects such as travel distance, consumption level, number of passengers and the like. However, not all users can fully know all travel services, and users cannot accurately find suitable travel services from the travel services.

In order to enable a user to use a better travel service, some travel service recommendation systems recommend a travel service with a higher recommendation rate to the user.

Disclosure of Invention

In view of the above, an object of the present application is to provide a travel recommendation method, an apparatus, an electronic device and a computer-readable storage medium, so as to improve the recommendation accuracy of a travel service.

In a first aspect, an embodiment of the present application provides a method for recommending travel services, including:

acquiring travel scene information of a position where a service requester places a travel order and supply and demand conditions of each travel service;

determining the acceptance probability of the service requester to each travel service according to the travel scene information;

and selecting a target travel service recommended to the service requester from the plurality of travel services according to the acceptance probability of the service requester to each travel service and the supply and demand conditions of each travel service.

With reference to the first aspect, an embodiment of the present application provides a first possible implementation manner of the first aspect, where the obtaining of the travel scene information of the location where the service requester places the travel order and the supply and demand conditions of each travel service includes:

responding to order operation information input by a service requester, and determining a trip order issuing stage;

if the trip order issuing stage is a target issuing stage, acquiring trip scene information of a position where the service requester issues the trip order and supply and demand conditions of each trip service; the stage of placing the travel order comprises at least one or more of the following: the method comprises a service starting position stage of placing a travel order, a service ending position stage of placing the travel order, a service starting time stage of placing the travel order, a service ending time stage of placing the travel order and a travel service type stage.

With reference to the first aspect, an embodiment of the present application provides a second possible implementation manner of the first aspect, where the travel scene information includes at least one or more of the following: characteristic information, traffic environment information, and weather environment information of the service requester.

With reference to the second possible implementation manner of the first aspect, an embodiment of the present application provides a third possible implementation manner of the first aspect, where the feature information of the service requester includes at least one or more of the following: age, gender, occupation, frequent residence, frequent trip, historically selected travel services, historical order amounts, and historical travel durations.

With reference to the first possible implementation manner of the first aspect, an embodiment of the present application provides a fourth possible implementation manner of the first aspect, where the stage of issuing the travel order includes a stage of service starting time for issuing the travel order and a stage of service starting position for issuing the travel order;

the determining, according to the travel scene information, an acceptance probability of the service requester for each travel service includes:

acquiring the predicted time for each service provider of the travel service to reach the service starting position;

and determining the acceptance probability of the service requester to each travel service according to the service starting time of the travel order and the predicted time of the service provider of each travel service reaching the service starting position.

With reference to the first possible implementation manner of the first aspect, an embodiment of the present application provides a fifth possible implementation manner of the first aspect, where the stage of issuing the travel order includes a stage of issuing a service start position of the travel order and a stage of issuing a service end position of the travel order;

determining the estimated travel resource consumption of each travel service according to the service starting position of the travel order and the service ending position of the travel order;

and determining the acceptance probability of the service requester to each travel service according to the estimated travel resource consumption and the travel scene information.

With reference to the fifth possible implementation manner of the first aspect, an embodiment of the present application provides a sixth possible implementation manner of the first aspect, where the estimated travel resource consumption includes at least one or more of the following: and estimating the amount of the order, the trip time and the trip mileage.

With reference to the first aspect, an embodiment of the present application provides a seventh possible implementation manner of the first aspect, where the method further includes:

pushing recommendation information for the target travel service to the service requester;

responding to a travel order issuing request of the service requester for the target travel service, and generating a travel order of the target travel service;

and dispatching the travel order to a service provider in an area where the service requester is located.

With reference to the seventh possible implementation manner of the first aspect, an embodiment of the present application provides an eighth possible implementation manner of the first aspect, where the pushing recommendation information for the target travel service to the service requester includes:

pushing recommendation information aiming at the target travel service to the service requester according to a preset recommendation mode; the preset recommendation mode comprises at least one or more of the following: recommendation time, recommendation frequency, and recommendation form.

With reference to the eighth possible implementation manner of the first aspect, an embodiment of the present application provides a ninth possible implementation manner of the first aspect, where the target travel service is a travel service with a lowest estimated travel resource consumption; the pushing recommendation information for the target travel service to the service requester according to a preset recommendation mode includes:

and pushing recommendation information for the trip service with the lowest estimated trip resource consumption to the service requester according to a preset recommendation frequency.

With reference to the first aspect, an embodiment of the present application provides a tenth possible implementation manner of the first aspect, where the determining, according to the travel scenario information, an acceptance probability of the service requester for each travel service includes:

inputting the travel scene information into a trained acceptance probability determination model to obtain the acceptance probability of each travel service of the service requester;

the trained acceptance probability determination model is obtained by the following steps:

obtaining a training sample; the training sample comprises sample travel scene information and sample acceptance probability; the sample receiving probability is the receiving probability of each travel service of the service requester under the sample travel scene information;

inputting the training sample into an untrained acceptance probability determination model for training so that the untrained acceptance probability determination model obtains the acceptance probability of the service requester to each travel service according to the sample travel scene information.

In a second aspect, an embodiment of the present application further provides a travel service recommendation device, including:

the system comprises an acquisition module, a processing module and a display module, wherein the acquisition module is used for acquiring travel scene information of a position where a service requester places a travel order and supply and demand conditions of each travel service;

the first determining module is used for determining the acceptance probability of the service requester to each travel service according to the travel scene information;

and the selection module is used for selecting a target travel service recommended to the service requester from the plurality of travel services according to the acceptance probability of the service requester on each travel service and the supply and demand conditions of each travel service.

In a third aspect, an embodiment of the present application further provides an electronic device, including: a processor, a memory and a 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 running, the machine-readable instructions when executed by the processor performing the steps of the first aspect described above, or any possible implementation of the first aspect.

In a fourth aspect, this application further provides a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor to perform the steps in the first aspect or any one of the possible implementation manners of the first aspect.

In a fifth aspect, this application further provides a computer program product, which includes a computer program or instructions, and when the computer program or instructions are executed by a processor, the steps in the first aspect or any possible implementation manner of the first aspect are implemented.

The travel service recommendation method provided by the embodiment of the application comprises the following steps: acquiring travel scene information of a position where a service requester places a travel order and supply and demand conditions of each travel service; determining the acceptance probability of the service requester to each travel service according to the travel scene information; and selecting a target travel service recommended to the service requester from the plurality of travel services according to the acceptance probability of the service requester to each travel service and the supply and demand conditions of each travel service. According to the method and the device, the influence of the travel scene information on the receiving probability of each travel service by the service requester and the supply and demand conditions of each travel service are considered, the target travel service with the receiving probability and the supply and demand conditions both meeting the travel demand of the service requester recommended by the service requester is recommended to the service requester, and therefore the recommendation accuracy of the travel service can be improved.

According to the travel service recommendation method provided by the embodiment of the application, when the travel order is in different issuing stages, the travel scene information of the position where the service requester issues the travel order and the supply and demand conditions of each travel service can be obtained, the acceptance probability of the service requester to each travel service can be improved by improving the accuracy of the obtained travel scene information, and then the recommendation accuracy of the travel service can be improved.

According to the travel service recommendation method provided by the embodiment of the application, the accuracy of the determined acceptance probability of the service requester on each travel service is higher by acquiring different travel scene information, and the recommendation accuracy of the travel service can be further improved.

In order to make the aforementioned objects, features and advantages of the present application more comprehensible, preferred embodiments accompanied with figures are described in detail below.

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 is a flowchart illustrating a method for recommending travel services according to an embodiment of the present application;

FIG. 2 illustrates a flow chart of an acceptance probability determination model training provided by an embodiment of the present application;

fig. 3 is a schematic structural diagram illustrating a first travel service recommendation device provided in an embodiment of the present application;

fig. 4 is a schematic structural diagram illustrating a second travel service recommendation device provided in an embodiment of the present application;

fig. 5 shows a schematic structural diagram of an electronic device provided in an embodiment of the present application.

Detailed Description

In order to make the objects, 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 is obvious that the described embodiments are only a part of the embodiments of the present application, and not all 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.

In order to enable a user to use a better travel service, some travel service recommendation systems recommend a travel service with a higher recommendation rate to the user, and because the recommendation method does not consider the travel demand of the user in the current travel scene, the acceptance rate of the user on the recommended travel service is not high.

The travel demand and the transport capacity change condition of the user in the current travel scene are considered. Based on this, the embodiment of the application provides a method and a device for recommending travel services, which are described below through an embodiment.

For the convenience of understanding the present embodiment, a detailed description will be first given of the travel service recommendation method disclosed in the embodiment of the present application.

When recommending a travel service to a service requester, the recommendation can be made at different stages of issuing a travel order by the service requester, and specifically, the recommendation can be divided into at least the following three stages: the first stage, recommendation can be carried out before the service requester places a travel order; in the second stage, the recommendation can be carried out before the service requester places the travel order; and in the third stage, the recommendation can be carried out after the service requester places the travel order.

For the condition that the recommendation is performed before the service requester places the trip order in the first stage, the recommendation is performed before the service requester places the trip order, and the recommendation may be performed after the service requester opens the application having the trip service function and before the service requester places the trip order. After the application program with the travel service function is opened by the service requester and before the service requester places the travel order, because the travel order is not generated, the detailed information of the travel order, namely the order operation information, cannot be obtained, so that when the travel service is recommended to the service requester, the historical travel demand of the service requester can be determined according to the order operation information of the historical travel order of the service requester, the current travel demand of the service requester is predicted, and the recommendation of the travel service is realized. However, in consideration of the fact that the current travel demand of the service requester is predicted according to the historical travel demand, errors may exist, and accurate recommendation cannot be performed on the service requester, so that the predicted current travel demand of the service requester is recommended at this time, and the accuracy of the acceptance probability of the service requester on the recommended travel service is not high.

In the second stage, the service requester makes recommendations when making a trip order, and makes recommendations when making a trip order, which may mean that the service requester makes recommendations after making a trip order and before paying a trip order, and the details of the trip order, that is, order operation information, can be obtained after the service requester makes a trip order.

In the third stage, the service requester makes a recommendation after issuing a travel order, which may mean that the service requester makes a recommendation after paying a travel order, and the generated travel order is already distributed to the service provider in consideration of that the travel order may have been generated according to order operation information issued by the service requester at this time. Considering that the above process is complex in operation, the probability that the service requester receives the recommended travel order at this time is low, and considering that the above process has the problem of wasting service resources, the rate of the travel order is reduced to some extent.

The travel service recommendation method provided by the embodiment of the application can be applied to the process of issuing a travel order by the service requester, namely, the travel service recommendation can be performed on the service requester at the second stage of issuing a travel order by the service requester.

As shown in the flowchart of the travel service recommendation method in fig. 1, the method includes the following steps:

s101: acquiring travel scene information of a position where a service requester places a travel order and supply and demand conditions of each travel service;

s102: determining the acceptance probability of the service requester to each travel service according to the travel scene information;

s103: and selecting a target travel service recommended to the service requester from the plurality of travel services according to the acceptance probability of the service requester to each travel service and the supply and demand conditions of each travel service.

According to the travel service recommendation method provided by the embodiment of the application, the receiving probability of the service requester to each travel service is determined according to the travel scene information of the position of the service requester when the service requester places the travel order, so that the determined receiving probability can better accord with the travel scene of the position of the service requester when the service requester places the travel order, the supply and demand conditions of each travel service are considered, and the accuracy of the receiving probability of the service requester to the recommended target travel service is higher.

The travel service may refer to a service provided by the service provider to the service requester to satisfy the travel requirement of the service requester. The travel services may include carpooling, express, special, tailgating, taxis, and the like. The service requester can place a travel order for the selected travel service, and the travel service platform can provide the travel service capable of executing the travel order to the service requester after placing the travel order.

In step S101, since the embodiment of the present application recommends a trip service for the service requester during the process of issuing a trip order by the service requester, in a feasible implementation manner, the execution subject of the embodiment of the present application may determine an issuing stage of the trip order in response to order operation information input by the service requester; and if the issuing stage of the travel order is the target issuing stage, acquiring travel scene information of the position where the service requester issues the travel order and the supply and demand conditions of each travel service.

The order operation information service requester performs order input operation information at the terminal, and the order operation information may include a service start position, a service end position, a service start time, a service end time, a travel service type, and the like. According to the order operation information input by the service requester, the issuing stage of the travel order can be determined. The issuing stage of the travel order corresponds to the order operation information input by the service requester. Thus, the stage of placing the travel order includes at least one or more of: the method comprises a service starting position stage of placing a travel order, a service ending position stage of placing the travel order, a service starting time stage of placing the travel order, a service ending time stage of placing the travel order and a travel service type stage of placing the travel order.

It should be noted here that the stage of placing the travel order is determined according to the order operation information that has been input by the service requester. For example, when the order operation information that has been input by the service requester includes a service start position and a service end position, the placing stage of the travel order includes a service start position stage for placing the travel order and a service end position stage for placing the travel order.

The phase of the service starting position for placing the travel order may refer to a phase of the service requester inputting the service starting position. The service initiation location may be a boarding location of the service requester. When the stage of issuing the travel order is the stage of the service starting position, it is indicated that the service requester may not select the travel service, and at this time, information such as travel scene information of the service starting position and supply and demand conditions of each travel service can be acquired according to the service starting position.

The service end location phase of placing the travel order may refer to a phase in which the service requester inputs the service end location. The service termination location of the travel order may refer to a location where the service requester disembarks. When the stage of issuing the travel order is the stage of the service termination position, it indicates that the service requester may not select the travel service, and at this time, the travel scene information of the service termination position and the information such as the supply and demand condition of each travel service can be acquired according to the service termination position.

The service starting position of the trip order and the service ending position of the trip order can be input to the trip order placing interface by the service requester through a manual input mode, can also be selected by the service requester on a map of the trip order placing interface, and can also be selected by the service requester according to the service starting position and/or the service ending position of the historical trip order.

Therefore, when the stage of placing the travel order includes a service starting position stage and/or a service ending position stage, the supply and demand condition of each travel service at the service starting position and/or the service ending position, the travel scene information of the service starting position and/or the service ending position, and the like can be acquired according to the service starting position and/or the service ending position.

The service start time phase of placing the travel order refers to a phase in which the service requester inputs the service start time. The service start time of the travel order may refer to a time when the service requester gets on the bus, and the service end time of the travel order may refer to a time when the service requester gets off the bus; the service start time of the travel order may also refer to the time when the service provider receives the travel order and confirms execution.

The service end time phase of placing the travel order refers to the phase of the service requester inputting the service end time. The end-of-service time of the travel order may also refer to the time the service provider confirms the order is completed. The service starting time and the service ending time of the trip order can be input into a trip order issuing interface by a service requester in a manual input mode, and can also be estimated by a trip service platform according to the time for the trip order to be issued by the service requester, the service starting position of the trip order, the service ending position of the trip order, the distance information from the position where the trip order is issued by the service requester to the service starting position, the distance information from the service provider to the service starting position of the trip order, and the like.

When the issuing stage of the travel order includes a service starting time stage and/or a service ending time stage, the supply and demand condition of each travel service at the service starting time and/or the service ending time, the travel scene information of the service starting time and/or the service ending time, and the like can be acquired according to the service starting time and/or the service ending time.

The trip service type issuing stage may refer to a stage in which a service provider selects a vehicle type expected to be used when executing a trip order issued by a service requester, and the trip service type may be input by the service requester according to history preference or trip demand, may be selected by the service requester from trip service types provided by a trip service platform, or may be a trip service type matched with the service requester for the trip service platform according to a trip service expected to be used by the service requester.

In a specific implementation process, when the issuing stages of the travel orders are different, the obtained travel scene information of the position where the service requester issues the travel orders and the supply and demand conditions of each travel service are also different. According to the method and the device, through the issuing stage of the travel orders, the travel service or the travel demand which is expected to be used by the service requester currently can be determined, so that the recommendation accuracy of the service requester is improved. For example, when the stage of issuing the travel order is the stage of issuing the travel service type, it indicates that the service requester has selected the travel service desired to be used, and when the service requester is recommended, the service requester can be recommended according to the travel service type. For example, when the stage of issuing the travel order includes a stage of service starting time for issuing the travel order and a stage of service ending time for issuing the travel order, the expected service duration of the service requester is described, and at this time, the service requester can be recommended according to the expected service duration.

When the number of the included travel orders is more, the more the acquired travel scene information of the position where the service requester places the travel orders and the supply and demand conditions of each travel service are, and the more accurate the acceptance probability of the service requester to each travel service is determined according to the travel scene information.

In general, there may be no chronological order between the different delivery stages. In some possible embodiments, the phase of placing the travel order at the service start position, the phase of placing the travel order at the service end position, the phase of placing the travel order at the service start time, and the phase of placing the travel order at the service end time may be before the phase of placing the travel service type, mainly because it is possible to determine whether there is a travel service type according to the service position and the service time. Therefore, in the embodiment of the present application, preferably, the phase of placing the service starting position of the travel order, the phase of placing the service ending position of the travel order, the phase of placing the service starting time of the travel order, and the phase of placing the service ending time of the travel order may be before the phase of placing the travel service type, so that the travel service may be recommended to the service requester before the phase of placing the travel service type by the service requester.

The location of the service requester may include street information, surrounding building information, geographical coordinate information, etc. where the service requester is located. The position information of a terminal used when a service requester places a travel order can be obtained through a positioning technology, and then the position of the service requester is determined according to the position information of the terminal; the position of the service requester can be determined according to the service starting position contained in the travel order issued by the service requester. In the implementation process, the service requester generally places the travel order by means of short-range control of the terminal (for example, operating the handheld mobile terminal), so that it can be considered that the location information of the terminal is the location of the service requester, and the service starting location included in the travel order is not necessarily the location of the service requester, so that there may be an error in the location of the service requester determined by the service starting location. Therefore, preferably, the location information of the terminal used when the service requester places the travel order may be obtained through a positioning technology, and then the location of the service requester is determined according to the location information of the terminal.

The travel scene information is scene information of a position where the service requester places a travel order, and the travel scene information may affect a travel service selected by the service requester, and specifically the travel scene information may include at least one or more of the following: characteristic information of a service requester, traffic environment information, and weather environment information.

Specifically, the feature information of the service requester may include at least one or more of the following: age, gender, occupation, frequent residence, frequent trip, historically selected travel services, historical order amounts, and historical travel durations.

Wherein, the age, sex and occupation can influence the selected travel service of the service requester, and the selected travel service can be different for different service requesters with different ages, sexes and occupations.

The frequent residence refers to a residence where the service requester frequently resides at present, and the frequent trip refers to a place where the service requester frequently trips. Through the frequent residence and frequent trip places of the service requester, the trip service that the service requester desires to use can be determined.

The historically selected travel service can refer to the travel service with the highest historical selection frequency of the service requester or the travel service selected last time in history; the travel service selected according to the history can be determined according to the travel service currently expected to be selected by the service requester.

The historical order amount may refer to an average amount of historical travel orders of the service requester or a maximum amount of historical travel orders, and according to the historical order amount, an amount of travel orders which the service requester currently desires to pay may be determined, so that travel services which the service requester currently desires to select may be determined.

The historical trip duration may refer to an average trip duration of a historical trip order of the service requester or a longest trip duration of the historical trip order, and according to the historical trip duration, a currently expected trip duration of the service requester may be determined, so that a trip service currently expected to be selected by the service requester may be determined.

The traffic environment information may refer to traffic congestion conditions, and the traffic environment information and the weather environment information may influence the selection of the travel service by the service requester.

The supply and demand condition of the travel service may refer to supply and demand conditions of service providing resources for providing the travel service and service requesting resources for requesting the travel service, and specifically, the supply and demand condition of the travel service may refer to a supply and demand ratio of service providers to service requesters, that is, a ratio of the number of service providers to the number of service requesters. The supply and demand of the travel service may affect the use of the travel service by the service requester.

In step S102, the travel demands of the service requesters that can be met by different travel services are different, for example, the tailgating service can meet the requirement of the service requesters on the amount of travel orders, and the express can meet the requirement of the service requesters on the travel speed; the special car can meet the requirements of the service requester on the types of travel services, so that the service requester has different acceptance probability of each travel service under different travel scene information.

In one possible embodiment, the current issuing stage of the travel order is a service starting position stage of issuing the travel order: the travel order information comprises service starting time and a service starting position;

step S102, namely determining the probability of receiving each travel service by the service requester according to the travel scenario information, may include the following steps:

s1021: acquiring the predicted time for each service provider of travel service to reach a service starting position;

s1022: and determining the acceptance probability of each travel service for the service requester according to the service starting time and the predicted time for the service provider of each travel service to reach the service starting position.

In step S1021, the current location information of the service provider of each travel service may be obtained, and the time when the service provider of each travel service reaches the service start position may be predicted according to the current location information and the current speed information of the service provider of each travel service.

Here, the service provider of each travel service may be a service provider whose distance from the service start position is within a preset range, and it is mainly considered that when the distance between the service provider and the service start position exceeds the preset range, the time for the service provider to reach the service start position may be too long, which may reduce the probability of receiving each travel service by the service requester to a great extent, and obviously may lose the meaning of recommending the service requester.

When the number of the service providers is plural, the time when the service provider of each travel service reaches the service start position may refer to an average time, an effective time, a longest time, a shortest time, or the like when the service provider reaches the service start position.

In step S1022, the predicted closer the time when the service provider of each travel service reaches the service start position is to the service start time, that is, the predicted smaller the time difference between the time when the service provider of each travel service reaches the service start position and the service start time is, the higher the probability of acceptance of each travel service by the service requester may be.

In one possible implementation, the trip order placing stage comprises a service starting position stage for placing a trip order and a service ending position stage for placing a trip order;

s1023: determining the estimated travel resource consumption of each travel service according to the service starting position and the service ending position of the travel order;

s1024: and determining the acceptance probability of the service requester to each travel service according to the estimated travel resource consumption and the travel scene information.

In step S1023, the estimated travel resource consumption amount may refer to the amount of travel resources estimated to be consumed by the service requester when the service provider travels from a service start location to a service end location of the same travel order.

Specifically, the estimated travel resource consumption may include at least one or more of the following: and estimating the amount of the order, the travel time length, the travel mileage and the like. The larger the estimated order amount is, the longer the estimated trip time is, and the more the estimated trip mileage is, the larger the estimated trip resource consumption is.

The travel scene information may affect the estimated travel resource consumption, for example, the more serious the traffic jam is, the longer the time taken for the service provider to travel from the service starting position to the service ending position of the same travel order is, the longer the estimated travel time consumed by the service requester is.

In step S1024, the trip scene information may affect the probability of receiving the estimated trip resource consumption by the service requester. Here, the travel scene information may include at least one or more of feature information of the service requester, traffic environment information, and weather environment information.

When the trip scene information is the characteristic information of the service requester, the estimated trip resource consumption acceptance probability of the service requester for each trip service can be determined according to the characteristic information of the service requester, and then the estimated trip resource consumption acceptance probability of the service requester for each trip service is determined according to the estimated trip resource consumption and the estimated trip resource consumption acceptance probability of the service requester for each trip service.

When the travel scene information is traffic environment information and/or weather environment information, the traffic environment information and/or the weather environment information may affect the estimated travel resource consumption acceptance probability of each travel service for the service requester, and further, the acceptance probability of each travel service for the service requester may be determined according to the estimated travel resource consumption and the estimated travel resource consumption acceptance probability of each travel service for the service requester under the traffic environment information and/or the weather environment information.

The more information included in the travel scene information, the more accurate the determined acceptance probability of the service requester for the estimated travel resource consumption of each travel service, and thus the more accurate the determined acceptance probability of the service requester for each travel service.

the travel scene information comprises characteristic information of a service requester; the characteristic information of the service requester comprises historical order amount;

s1025: determining the estimated order amount of each travel service according to the service starting position of the travel order and the service ending position of the travel order;

s1026: and determining the acceptance probability of the service requester to each travel service according to the estimated order amount and the historical order amount.

In step S1025, the estimated order amount of each travel service is determined according to the service start position and the service end position of the same travel order, and the estimated order amount of different travel services may be calculated in different manners. Therefore, according to the service starting position and the service ending position of the same trip order, the pricing mode that the service provider travels from the service starting position to the service ending position of the same trip order is determined, and according to the pricing mode that the service provider travels from the service starting position to the service ending position of the same trip order, the estimated order amount of each trip service is determined.

In step S1026, the historical order amount may refer to an average amount of the historical trip orders of the service requester or a maximum amount of the historical trip orders. Wherein the service start position and the service end position of the historical travel order are the same as the service start position and the service end position of the travel order in step S1026, respectively.

By comparing the estimated order amount with the historical order amount, the probability of acceptance of each travel service by the service requester can be determined.

In one possible implementation, the trip order placing stage comprises a service starting position stage for placing a trip order and a service ending position stage for placing a trip order; the travel scene information includes: characteristic information and traffic environment information of a service requester; the user characteristic information includes: the historical trip duration;

step S102, namely determining the probability of receiving each travel service by the service requester according to the travel scenario information, specifically including the following steps:

s1027: determining the estimated travel time of each travel service from the service starting position to the service ending position according to the traffic environment information, the service starting position of the travel order and the service ending position of the travel order;

s1028: and determining the acceptance probability of the service requester to each travel service according to the estimated travel time and the historical travel time.

In step S1027, according to the service start position and the service end position of the travel order, mileage information of the service provider traveling from the service start position to the service end position of the same travel order may be determined. According to the traffic environment information, the speed information of different service providers driving from the service starting position to the service ending position of the same trip order can be determined, and according to the mileage information of the service providers driving from the service starting position to the service ending position of the same trip order and the speed information of the service providers driving from the service starting position to the service ending position of the same trip order, the estimated driving time of each service provider of trip service from the same service starting position to the service ending position can be determined.

In step S1028, the historical trip duration may refer to an average trip duration of the historical trip orders of the service requester or a longest trip duration of the historical trip orders, where a service start location and a service end location of the historical trip orders are respectively the same as the service start location and the service end location of the trip orders.

By comparing the estimated travel time length with the historical travel time length, the probability of receiving each travel service by the service requester can be determined.

In a specific embodiment, according to different trip scene information, a current trip demand of a service requester can be determined, and specifically, the current trip demand of the service requester can be determined according to at least one or more of characteristic information, traffic environment information, and weather environment information of the service requester. The travel demand can be a demand for reducing travel cost, travel time, travel mileage and the like. According to the current trip demand of the service requester, under the conditions of the estimated order amount, the estimated trip time and the estimated trip mileage of each trip service from the same service starting position to the same service ending position, the service requester receives the probability of each trip service. When the current travel demands of the service requesters are different, the acceptance probability of each travel service by the service requesters is different.

For example, when the current trip demand of the service requester is trip cost reduction, the service requester may prefer to select a trip service with a low estimated order amount, and consider less the problems of estimated trip duration and estimated trip mileage. Therefore, the probability of accepting the trip service with a service requester with a lower estimated order amount but a higher estimated trip duration and estimated trip mileage may be higher.

In one possible implementation, the trip order placing stage comprises a service starting position stage for placing a trip order and a service ending position stage for placing a trip order; the travel scene information includes: traffic environment information; step S102, namely determining the probability of receiving each travel service by the service requester according to the travel scenario information, specifically including the following steps:

s1029: determining the estimated travel mileage of each travel service from the service starting position to the service ending position according to the traffic environment information, the service starting position of the travel order and the service ending position of the travel order;

s10210: and determining the acceptance probability of each travel service of the service requester according to the estimated travel mileage, the service starting position of the travel order and the service ending position of the travel order.

In step S1029, according to the traffic environment information, route information of the service provider traveling from the service start position of the travel order to the service end position of the travel order may be determined, and according to the route information of the service provider traveling from the service start position of the travel order to the service end position of the travel order, an estimated travel mileage of the service provider of each travel service from the service start position to the service end position may be determined.

In step S10210, according to the service start position of the travel order and the service end position of the travel order, the shortest mileage information from the travel order service start position to the travel order service end position of the service provider can be determined.

According to the estimated travel mileage and the shortest mileage information from the travel order service starting position to the travel order service ending position of the service provider, the probability of each travel service received by the service requester can be determined.

In a specific implementation process, step S102 may be performed by an acceptance probability determination model, and specifically, the travel scenario information may be input into the trained acceptance probability determination model, so as to obtain an acceptance probability of the service requester for each travel service.

The trained acceptance probability determination model can be obtained by the following steps:

s201: obtaining a training sample; the training sample comprises sample travel scene information and sample receiving probability; the sample acceptance probability is the acceptance probability of the service requester to each travel service in the sample travel scene;

s202: and inputting the training samples into the untrained acceptance probability determination model for training so as to obtain the acceptance probability of the service requester to each travel service according to the travel scene information of the samples by the untrained acceptance probability determination model.

In step S201, the sample travel scene information may include at least one or more of the following: characteristic information, traffic environment information and weather environment information of the service requester; wherein the characteristic information of the service requester comprises at least one or more of the following: age, gender, occupation, frequent residence, frequent trip, historically selected travel services, historical order amounts, and historical travel durations.

When the sample travel scene information in the training sample is the same, the same sample travel scene information may correspond to different travel services. When the travel services in the training samples are different, the same travel service can correspond to different sample travel scene information.

In a specific implementation process, the sample travel scene information can be classified to obtain characteristic information, traffic environment information and weather environment information of the service requester, and for each type of sample travel scene information, the sample travel scene information with the largest influence on the acceptance probability of the service requester on each travel service can be selected from the type of sample travel scene information. The sample travel scene information with the largest influence on the acceptance probability of each travel service by the service requester can be obtained according to historical experience, or can be obtained according to a preset algorithm, and is not described in detail herein.

And taking the acceptance probability corresponding to the sample travel scene information with the largest influence of the service requester on the acceptance probability of each travel service in each type of sample travel scene information as the acceptance probability of each travel service by the service requester under the sample travel scene information.

In step S202, for each type of sample travel scene information, as in the received probability determination model training flowchart shown in fig. 2, under the sample travel scene information of each type selected in step S201 and the sample travel scene information of that type, the service requester may input the received probability of each travel service into different sub-models respectively, and train each sub-model, so that each sub-model obtains the received probability of each travel service under the sample travel scene information of that type according to the sample travel scene information of each type.

After the acceptance probability of the service requester to each travel service under each type of sample travel scene information is obtained, the total acceptance probability of the service requester to each travel service under the sample travel scene information can be obtained according to the weight of each acceptance probability, so that the training of an untrained acceptance probability determination model is realized.

In step S103, the target travel service refers to a travel service selected for recommendation to the service requester. The receiving probability of the service requester to the target travel service is larger than a certain threshold value, and the supply of the target travel service meets the travel requirement of the service requester.

As described above, the supply and demand situation of the travel service may refer to the supply and demand situation of the service providing resource providing the travel service and the service requesting resource requesting the travel service. In the specific implementation process, when the probability of receiving a certain travel service by a service requester is high, if a service providing resource is smaller than the service requesting resource, that is, the supply is smaller than the demand, even if the travel service is recommended to the service requester, the travel service is likely to fail to meet the travel demand of the service requester, so that not only is the service resource wasted, but also the transaction rate of a travel order is reduced. Therefore, when selecting the target travel service recommended to the service requester, the acceptance probability of the service requester to each travel service and the supply and demand condition of each travel service need to be considered at the same time.

In one possible implementation, the supply and demand condition of each travel service may refer to the supply and demand ratio of the service provider to the service requester, i.e. the ratio of the number of service providers to the number of service requesters. Step S103 may be performed according to the following steps:

s1031: selecting a first travel service with the probability of being accepted by a service requester for the travel service larger than a first threshold from a plurality of travel services;

s1032: selecting a second travel service from the first travel service, wherein the ratio of the number of service providers to the number of service requesters is greater than a second threshold;

s1033: and determining the second travel service as a target travel service recommended to the service requester.

In step S1031, the first travel service refers to a travel service in which the probability of acceptance of the travel service by the service requester is greater than the first threshold, but includes different supply and demand situations, and therefore, in step S1032, a further selection is made from the first travel service, and the selected second travel service is a travel service in which the probability of acceptance of the travel service by the service requester is greater than the first threshold and the ratio of the number of service providers to the number of service requesters is greater than the second threshold. The target travel service in step S303 meets both the acceptance condition of the service requester to the target travel service and the demand and supply requirements of the service requester.

In a specific implementation process, in step S1032, there may be a case where a ratio of the number of service providers to the number of service requesters is not greater than a second threshold, that is, a second travel service where the ratio of the number of service providers to the number of service requesters is greater than the second threshold cannot be selected from the first travel service, but considering that the probability of receiving the travel service by the service requester is greater than the first threshold, the condition that the service requester receives the first travel service is satisfied, which indicates that the service requester has a greater willingness to receive the first travel service, and therefore there may be a case where the ratio of the number of service providers received by the service requester to the number of service requesters is not greater than the second threshold, and therefore, the first travel service at this time may be used as a target travel service recommended to the service requester.

Correspondingly, in a possible embodiment, step S103 may be performed according to the following steps:

s1034: selecting a first travel service from the plurality of travel services, wherein the ratio of the number of service providers to the number of service requesters is greater than a first threshold;

s1035: selecting a second travel service with the travel service acceptance probability of the service requester being greater than a second threshold from the first travel service;

s1036: and determining the second travel service as a target travel service recommended to the service requester.

In step S1034, the first travel service refers to a travel service in which the ratio of the number of service providers to the number of service requesters is greater than the first threshold, but at the same time, different acceptance probabilities are included, and therefore, in step S1035, a further selection is made from the first travel service, and the selected second travel service is a travel service in which the ratio of the number of service providers to the number of service requesters is greater than the first threshold and the acceptance probability of the service requesters for the travel service is greater than the second threshold. The target travel service in step S1036 meets both the acceptance condition of the service requester to the target travel service and the supply and demand requirements of the service requester.

In a specific implementation process, in step S1035, there may be a case where the probability of accepting the travel service by the service requester is not greater than the second threshold, that is, a second travel service for which the probability of accepting the travel service by the service requester is not greater than the first threshold, that is, a travel service for which the ratio of the number of service providers to the number of service requesters is greater than the first threshold and the probability of accepting the travel service by the service requester is not greater than the second threshold.

Considering that when the probability of receiving the travel service by the service requester is not greater than the first threshold, it indicates that the willingness of the service requester to receive the target travel service is small, and even if the first travel service meets the supply and demand requirements of the service requester, but cannot meet the condition of receiving the first travel service by the service requester, when the first travel service is recommended to the service requester, the service requester may not receive the first travel service, and therefore the target travel service recommended to the service requester may not be selected in such a case.

It can be seen that compared with the processes of steps S1034-S1036, the processes of steps S1031-S1033 described above have higher probability of accepting the travel service by the service requester.

In a possible implementation manner, after step S103 is executed, the method for recommending travel service provided in an embodiment of the present application further includes:

s301: pushing recommendation information aiming at the target travel service to a service requester;

s302: a response service requester makes a request for a travel order of the target travel service, and generates a travel order of the target travel service;

s303: and dispatching the travel order to the service provider in the area where the service requester is located.

In step S301, the recommendation information refers to information pushed to the service requester recommending that the service requester use the target travel service.

The recommendation information may include at least one or more of the following: the supply and demand conditions of the target trip service, the estimated trip resource consumption of the target trip service and the like.

As mentioned above, the supply and demand condition of the target travel service may refer to the supply and demand condition of the service providing resource providing the target travel service and the service requesting resource requesting the target travel service, and specifically, the supply and demand condition of the target travel service may refer to the supply and demand ratio of the service providers and the service requesters, that is, the ratio of the number of the service providers to the number of the service requesters.

The estimated travel resource consumption of the target travel service may include at least one or more of the following: and estimating the amount of the order, the travel time length, the travel mileage and the like.

In a specific implementation process, when step S301 is executed, recommendation information for a target travel service may be pushed to a service requester in a preset recommendation manner; the preset recommendation mode comprises at least one or more of the following: recommendation time, recommendation frequency, and recommendation form.

The preset recommendation mode may be a recommendation mode which is preset at the terminal by the service requester and indicates that the service requester can accept, or a recommendation mode which is set by the travel service platform according to different target travel services.

Wherein, the recommendation time refers to the time of recommending to the service requester. In consideration of the willingness of the service requester to receive the recommendation, the recommendation time is set, the recommendation can be made to the service requester at the time when the service requester receives the recommendation, and the probability of receiving the target travel service by the service requester can be improved.

In addition, the target service recommendation is performed to the service requester when the service requester places the travel order, so that the recommendation time can be set according to the time when the service requester places the travel order, and here, the recommendation time can be set in the process of placing the travel order by the service requester. When the recommending time is later than the process of the service requester for issuing the travel order, for example, after the service requester issues the travel order, the service requester may not issue the travel order again, which does not play a recommending role, and cannot improve the probability of the service requester for receiving the target travel service.

The recommended frequency refers to a frequency of recommending to the service requester within a preset time period. The recommendation frequency may be determined according to the recommendation times and the recommended preset time period. The recommended preset time period may be set in the process of placing the travel order by the service requester.

The recommended form refers to a form in which a recommendation is made to a service requester. The recommended form may include a pop-up window, a bar, a bubble, a short message, etc.

In a specific implementation process, the recommendation time, the recommendation frequency and the recommendation form can be combined at will.

In a feasible implementation manner, the target travel service is a travel service with the lowest estimated travel resource consumption, and the pushing of recommendation information for the target travel service to the service requester according to a preset recommendation manner may specifically include: and according to the preset recommendation frequency, recommending information aiming at the travel service with the lowest estimated travel resource consumption is pushed to the service requester.

When the target trip service is a trip service with the lowest estimated trip resource consumption, that is, the estimated trip resource consumption, for example: the estimated order amount, the estimated trip duration, the estimated trip mileage and other minimum consumptions are the lowest, and considering that the service requester has a high probability of receiving the trip service with the lowest estimated trip resource consumption, the service requester can be timely recommended to the service requester according to the preset recommendation frequency, so that the service requester can timely receive the recommendation information.

In step S302, the executive body according to the embodiment of the application may generate a trip order of the target trip service according to the order operation information and the target trip service issued by the service requester after the service requester issues a request for a trip order of the target trip service.

The generated travel order of the target travel service may include order operation information and the selected target travel service. Wherein the order operation information comprises at least one or more of the following: the travel order issuing time, the travel order service starting position, the travel order service ending position, the travel order service starting time, the travel order service ending time and the like.

In step S303, the service provider may be a provider that can only provide the target travel service, or may be a provider that provides a plurality of travel services including the target travel service.

In a specific implementation process, the position information of the service provider can be acquired through a positioning technology, and the service provider in the area where the position of the service requester belongs can be selected according to the position information.

The delivery mode of the travel order can comprise broadcast delivery and designated delivery.

In a possible implementation manner, when the number of service providers in the area where the service requester is located belongs to is multiple, the service providers can be distributed in a broadcast distribution manner; when there is one service provider in the area where the service requester is located, the service provider can be distributed in a designated distribution manner.

In a feasible implementation manner, when a plurality of service providers are provided in an area to which the service requester is located, the service providers can be ranked according to the distance between each service provider and the location where the service requester is located, and the service providers with the distance between the service provider and the location where the service requester is located being smaller than a preset distance are used as target service providers and can be distributed to the target service providers in a broadcast distribution manner; the service provider with the minimum distance from the service requester can also be assigned by way of the designated dispatch.

It should be noted that all ways of dispatching a row order to a service provider in an area of a location of a service requester should be within the scope of the present application.

After step S103, the embodiment of the present application may further include the following steps:

s401: acquiring an optimal travel route corresponding to a target travel service; the optimal travel route is the travel route with the shortest route in the travel routes from the service starting position of the travel order to the service ending position of the travel order;

s402: and recommending the optimal travel route to the service requester.

In step S401, a plurality of travel routes corresponding to the target travel service may be obtained, and according to a distance from the service start position of the travel order to the service end position of the travel order, a travel route with the shortest distance in the travel routes from the service start position of the travel order to the service end position of the travel order is used as an optimal travel route.

In step S402, the optimal travel route may be recommended while the target travel service is recommended to the service requester, or the optimal travel route may be recommended after the service requester makes a request for a travel order of the target travel service.

By recommending the optimal travel route to the service requester, the service requester can select the optimal target travel service and the optimal travel route at the same time, so that the acceptance probability of the service requester on the target travel service is improved.

Based on the same technical concept, embodiments of the present application further provide a travel service recommendation device, an electronic device, a computer-readable storage medium, and the like, which may be referred to in the following embodiments.

Fig. 3 is a block diagram illustrating a travel service recommendation apparatus according to some embodiments of the present application, which implements functions corresponding to the above-described steps of executing a travel service recommendation method on a terminal device. The device may be understood as a component of a server including a processor, which is capable of implementing the above travel service recommendation method, as shown in fig. 3, the travel service recommendation device may include:

the first obtaining module 31 is configured to obtain travel scene information of a location where the service requester places a travel order and a supply and demand condition of each travel service;

a first determining module 32, configured to determine, according to the trip scene information, an acceptance probability of each trip service by the service requester;

a selecting module 33, configured to select a target travel service recommended to the service requester from the plurality of travel services according to the acceptance probability of the service requester for each travel service and the supply and demand conditions of each travel service.

In a possible implementation, as shown in fig. 4, the first obtaining module 31 includes:

a second determining module 311, configured to determine, in response to the order operation information input by the service requester, a stage of issuing the travel order;

a second obtaining module 312, configured to obtain, if the trip order issuing stage is a target issuing stage, trip scene information of a location where the service requester issues a trip order and a supply and demand condition of each trip service; the stage of placing the travel order comprises at least one or more of the following: the method comprises a service starting position stage of placing a travel order, a service ending position stage of placing the travel order, a service starting time stage of placing the travel order, a service ending time stage of placing the travel order and a travel service type stage.

In one possible embodiment, the travel scene information includes at least one or more of the following: characteristic information, traffic environment information, and weather environment information of the service requester.

In one possible embodiment, the feature information of the service requester includes at least one or more of the following: age, gender, occupation, frequent residence, frequent trip, historically selected travel services, historical order amounts, and historical travel durations.

In a feasible implementation manner, the trip order issuing stage comprises a service starting time stage of issuing a trip order and a service starting position stage of issuing a trip order;

the first determination module 32 includes:

the third obtaining module is used for obtaining the predicted time for each service provider of the travel service to reach the service starting position;

and a third determining module, configured to determine, according to the service start time of the travel order and the predicted time for the service provider of each travel service to reach the service start location, an acceptance probability of the service requester for each travel service.

In a possible embodiment, the trip order placing stage comprises a service starting position stage for placing a trip order and a service ending position stage for placing a trip order;

the first determination module 32 includes:

a fourth determining module, configured to determine an estimated travel resource consumption of each travel service according to a service start position of the travel order and a service end position of the travel order;

and a fifth determining module, configured to determine, according to the estimated travel resource consumption and the travel scene information, an acceptance probability of the service requester for each travel service.

In one possible embodiment, the travel service recommending apparatus further includes:

the pushing module is used for pushing recommendation information aiming at the target trip service to the service requester;

the response module is used for responding to a travel order issuing request of the service requester for the target travel service and generating a travel order of the target travel service;

and the dispatching module is used for dispatching the travel order to the service provider in the area where the service requester is located.

In a possible embodiment, the estimated travel resource consumption includes at least one or more of the following: and estimating the amount of the order, the trip time and the trip mileage.

In a possible implementation, the pushing module is specifically configured to: pushing recommendation information aiming at the target travel service to the service requester according to a preset recommendation mode; the preset recommendation mode comprises at least one or more of the following: recommendation time, recommendation frequency, and recommendation form.

In a possible implementation manner, the target trip service is a trip service with the lowest estimated trip resource consumption; the pushing module is specifically configured to: and pushing recommendation information for the trip service with the lowest estimated trip resource consumption to the service requester according to a preset recommendation frequency.

In a possible implementation manner, the first determining module is configured to input the travel scenario information into a trained acceptance probability determining model, so as to obtain an acceptance probability of each travel service for the service requester;

As shown in fig. 5, which is a schematic structural diagram of an electronic device 500 provided in an embodiment of the present application, the electronic device 500 includes: at least one processor 501, at least one network interface 504 and at least one user interface 503, memory 505, at least one communication bus 502. A communication bus 502 is used to enable connective communication between these components. The user interface 503 includes a display (e.g., a touch screen), a keyboard, or a pointing device (e.g., a touch pad or touch screen, etc.).

Memory 505 may include both read-only memory and random access memory and provides instructions and data to processor 501. A portion of the memory 505 may also include non-volatile random access memory (NVRAM).

In some embodiments, memory 505 stores the following elements, executable modules or data structures, or a subset thereof, or an expanded set thereof:

an operating system 5051, which includes various system programs for implementing various basic services and processing hardware-based tasks;

the application programs 5052 include various application programs for implementing various application services.

In the embodiment of the present application, by calling the program or instructions stored in the memory 505, the processor 501 is configured to:

In a possible implementation manner, the processor 501, when performing the steps to obtain the travel scene information of the location where the service requester places the travel order and the supply and demand situation of each travel service, is configured to:

when the processor 501 determines, according to the travel scenario information, the probability of receiving each travel service by the service requester, specifically:

the processor 501 determines, in an execution step, an acceptance probability of the service requester for each travel service according to the travel scenario information, and specifically is configured to:

In one possible implementation, the processor 501 is further configured to:

In a possible implementation manner, when the processor 501 executes the step of pushing the recommendation information for the target travel service to the service requester, the processor is specifically configured to:

In a possible implementation manner, the target trip service is a trip service with the lowest estimated trip resource consumption; when the execution step pushes recommendation information for the target travel service to the service requester in a preset recommendation manner, the processor 501 is specifically configured to:

In a possible implementation manner, the processor 501, in execution step, determines, according to the travel scenario information, a probability of acceptance of each travel service by the service requester, specifically to:

The computer program product for performing the travel service recommendation method provided in the embodiment of the present application includes a computer-readable storage medium storing a nonvolatile program code executable by a processor, where instructions included in the program code may be used to execute the method described in the foregoing method embodiment, and specific implementation may refer to the method embodiment, which is not described herein again.

It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

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 embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units 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 units through some communication interfaces, and may be in an electrical, mechanical or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units 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 usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.

Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present application, and are used for illustrating the technical solutions of the present application, but not limiting the same, and the scope of the present application is not limited thereto, and although the present application is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope disclosed in the present application; such modifications, changes or substitutions do not depart from the spirit and scope of the exemplary embodiments of the present application, and are intended to 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. The travel service recommendation method is characterized by comprising the following steps:

2. The method for recommending travel services according to claim 1, wherein said obtaining information of the travel scene at the location where the service requester places the travel order and the supply and demand conditions of each travel service comprises:

3. A travel service recommendation method according to claim 1, characterized in that said travel scenario information includes at least one or more of: characteristic information, traffic environment information, and weather environment information of the service requester.

4. A travel service recommendation method according to claim 3, characterized in that said service requester's characteristic information includes at least one or more of: age, gender, occupation, frequent residence, frequent trip, historically selected travel services, historical order amounts, and historical travel durations.

5. A travel service recommendation method according to claim 2, characterized in that said trip order placing phases comprise a trip order placing service start time phase and a trip order placing service start position phase;

6. A travel service recommendation method according to claim 2, characterized in that said trip order placing phases comprise a service starting position phase for placing a trip order and a service ending position phase for placing a trip order;

7. A travel service recommendation method according to claim 6, wherein said estimated travel resource consumption comprises at least one or more of: and estimating the amount of the order, the trip time and the trip mileage.

8. A travel service recommendation method according to claim 1, further comprising:

9. A travel service recommendation method according to claim 8, wherein said pushing recommendation information for said target travel service to said service requester comprises:

10. A travel service recommendation method according to claim 9, wherein the target travel service is a travel service with the lowest estimated travel resource consumption; the pushing recommendation information for the target travel service to the service requester according to a preset recommendation mode includes:

11. A travel service recommendation method according to claim 1, wherein said determining the probability of acceptance of each of said travel services by said service requester according to said travel scenario information comprises:

12. Travel service recommendation apparatus, characterized by comprising:

13. An electronic device, comprising: a processor, a memory and a 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 running, the machine readable instructions when executed by the processor performing the steps of the travel service recommendation method according to any one of claims 1 to 11.

14. A computer-readable storage medium, wherein a computer program is stored thereon, and when executed by a processor, the computer program performs the steps of the travel service recommendation method according to any one of claims 1 to 11.

15. A computer program product comprising a computer program or instructions for implementing the steps of the travel service recommendation method of any one of claims 1 to 11 when executed by a processor.