CN115292595A

CN115292595A - Information recommendation method and device, equipment and medium

Info

Publication number: CN115292595A
Application number: CN202210933597.XA
Authority: CN
Inventors: 韩雅娟
Original assignee: Beijing Baidu Netcom Science and Technology Co Ltd
Current assignee: Beijing Baidu Netcom Science and Technology Co Ltd
Priority date: 2022-08-04
Filing date: 2022-08-04
Publication date: 2022-11-04

Abstract

The disclosure provides an information recommendation method, an information recommendation device, information recommendation equipment and an information recommendation medium based on an electronic map, and relates to the technical field of computers, in particular to the technical field of intelligent recommendation. The implementation scheme is as follows: acquiring current position information of a target user and input travel destination information; determining a travel type of the target user based on the current position information and travel destination information of the target user, wherein the travel type comprises allopatric travel; and determining recommendation strategy information at least based on the travel type of the target user, wherein the recommendation strategy information comprises travel mode information and interest point information recommended to the target user.

Description

Information recommendation method and device, equipment and medium

Technical Field

The present disclosure relates to the field of computer technologies, and in particular, to an information recommendation method and apparatus based on an electronic map, an electronic device, a computer-readable storage medium, and a computer program product.

Background

With the popularization of the mobile-end electronic map application program, public transportation information, navigation service and other contents contained in the electronic map application program are increasingly browsed and used by a user, and the platform can also actively recommend information to the user so as to improve the user experience.

The approaches described in this section are not necessarily approaches that have been previously conceived or pursued. Unless otherwise indicated, it should not be assumed that any of the approaches described in this section qualify as prior art merely by virtue of their inclusion in this section. Similarly, unless otherwise indicated, the problems mentioned in this section should not be considered as having been acknowledged in any prior art.

Disclosure of Invention

The present disclosure provides an electronic map-based information recommendation method, apparatus, electronic device, computer-readable storage medium, and computer program product.

According to an aspect of the present disclosure, there is provided an electronic map-based information recommendation method, including: acquiring current position information of a target user and input travel destination information; determining a travel type of the target user based on the current position information and travel destination information of the target user, wherein the travel type comprises allopatric travel; and determining recommendation strategy information at least based on the travel type of the target user, wherein the recommendation strategy information comprises travel mode information and interest point information which are used for recommending the target user.

According to another aspect of the present disclosure, there is provided an electronic map-based information recommendation apparatus including: an acquisition unit configured to acquire current location information of a target user and input travel destination information; a first determining unit configured to determine a travel type of the target user based on current location information and travel destination information of the target user, the travel type including allopatric travel; and a second determining unit configured to determine recommendation policy information based on at least the travel type of the target user, the recommendation policy information including travel mode information and point of interest information for recommending to the target user.

According to another aspect of the present disclosure, there is provided an electronic device including: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the above information recommendation method.

According to another aspect of the present disclosure, there is provided a non-transitory computer-readable storage medium storing computer instructions for causing the computer to perform the above-described information recommendation method.

According to another aspect of the present disclosure, a computer program product is provided, comprising a computer program, wherein the computer program is capable of implementing the above-mentioned information recommendation method when executed by a processor.

According to one or more embodiments of the present disclosure, recommendation accuracy can be improved, and user experience is improved at the same time.

It should be understood that the statements in this section are not intended to identify key or critical features of the embodiments of the present disclosure, nor are they intended to limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the embodiments and, together with the description, serve to explain the exemplary implementations of the embodiments. The illustrated embodiments are for purposes of illustration only and do not limit the scope of the claims. Throughout the drawings, identical reference numbers designate similar, but not necessarily identical, elements.

FIG. 1 shows a schematic diagram of an exemplary system in which various methods described herein may be implemented, according to an exemplary embodiment of the present disclosure;

fig. 2 illustrates a flowchart of an electronic map-based information recommendation method according to an exemplary embodiment of the present disclosure;

fig. 3 illustrates a flowchart of an electronic map-based information recommendation method according to an exemplary embodiment of the present disclosure;

fig. 4 is a block diagram illustrating a structure of an electronic map-based information recommendation apparatus according to an exemplary embodiment of the present disclosure;

FIG. 5 illustrates a block diagram of an exemplary electronic device that can be used to implement embodiments of the present disclosure.

Detailed Description

Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which various details of the embodiments of the disclosure are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.

In the present disclosure, unless otherwise specified, the use of the terms "first", "second", etc. to describe various elements is not intended to limit the positional relationship, the timing relationship, or the importance relationship of the elements, and such terms are used only to distinguish one element from another. In some examples, a first element and a second element may refer to the same instance of the element, and in some cases, based on the context, they may also refer to different instances.

The terminology used in the description of the various described examples in this disclosure is for the purpose of describing particular examples only and is not intended to be limiting. Unless the context clearly indicates otherwise, if the number of elements is not specifically limited, the elements may be one or more. Furthermore, the term "and/or" as used in this disclosure is intended to encompass any and all possible combinations of the listed items.

In a map application program, different users usually have different requirements for contents such as travel mode information and interest point information. In the related art, information is generally recommended to a user based on a unified strategy, and the travel requirements of the user cannot be effectively and accurately identified and classified, and in this case, information which does not meet the requirements of the user may be recommended to the user, so that user experience is affected.

Based on the information recommendation method based on the electronic map, the travel type of the user is accurately identified by using the current position of the user and the input travel destination, particularly the user who travels in different places is identified, and therefore targeted recommendation is achieved, recommendation accuracy can be improved, and user experience is improved.

Embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings.

Fig. 1 illustrates a schematic diagram of an example system 100 in which various methods and apparatus described herein may be implemented in accordance with embodiments of the present disclosure. Referring to fig. 1, the system 100 includes one or

more client devices

101, 102, 103, 104, 105, and 106, a server 120, and one or more communication networks 110 coupling the one or more client devices to the server 120.

Client devices

101, 102, 103, 104, 105, and 106 may be configured to execute one or more applications.

In an embodiment of the present disclosure, the server 120 may run one or more services or software applications that enable the electronic map-based information recommendation method to be performed.

In some embodiments, the server 120 may also provide other services or software applications, which may include non-virtual environments and virtual environments. In some embodiments, these services may be provided as web-based services or cloud services, for example, provided to users of

client devices

101, 102, 103, 104, 105, and/or 106 under a software as a service (SaaS) model.

In the configuration shown in fig. 1, server 120 may include one or more components that implement the functions performed by server 120. These components may include software components, hardware components, or a combination thereof, which may be executed by one or more processors. A user operating a

client device

101, 102, 103, 104, 105, and/or 106 may, in turn, utilize one or more client applications to interact with the server 120 to take advantage of the services provided by these components. It should be understood that a variety of different system configurations are possible, which may differ from system 100. Accordingly, fig. 1 is one example of a system for implementing the various methods described herein and is not intended to be limiting.

The user may use

client devices

101, 102, 103, 104, 105, and/or 106 to input travel destination information. The client device may provide an interface that enables a user of the client device to interact with the client device. The client device may also output information to the user via the interface. Although fig. 1 depicts only six client devices, those skilled in the art will appreciate that any number of client devices may be supported by the present disclosure.

Client devices

101, 102, 103, 104, 105, and/or 106 may include various types of computer devices, such as portable handheld devices, general purpose computers (such as personal computers and laptop computers), workstation computers, wearable devices, smart screen devices, self-service terminal devices, service robots, gaming systems, thin clients, various messaging devices, sensors or other sensing devices, and so forth. These computer devices may run various types and versions of software applications and operating systems, such as MICROSOFT Windows, APPLE iOS, UNIX-like operating systems, linux, or Linux-like operating systems (e.g., GOOGLE Chrome OS); or include various Mobile operating systems such as MICROSOFT Windows Mobile OS, iOS, windows Phone, android. Portable handheld devices may include cellular telephones, smart phones, tablets, personal Digital Assistants (PDAs), and the like. Wearable devices may include head-mounted displays (such as smart glasses) and other devices. The gaming system may include a variety of handheld gaming devices, internet-enabled gaming devices, and the like. The client device is capable of executing a variety of different applications, such as various Internet-related applications, communication applications (e.g., email applications), short Message Service (SMS) applications, and may use a variety of communication protocols.

Network 110 may be any type of network known to those skilled in the art that may support data communications using any of a variety of available protocols, including but not limited to TCP/IP, SNA, IPX, etc. By way of example only, one or more networks 110 may be a Local Area Network (LAN), an ethernet-based network, a token ring, a Wide Area Network (WAN), the internet, a virtual network, a Virtual Private Network (VPN), an intranet, an extranet, a blockchain network, a Public Switched Telephone Network (PSTN), an infrared network, a wireless network (e.g., bluetooth, WIFI), and/or any combination of these and/or other networks.

The server 120 may include one or more general purpose computers, special purpose server computers (e.g., PC (personal computer) servers, UNIX servers, mid-end servers), blade servers, mainframe computers, server clusters, or any other suitable arrangement and/or combination. The server 120 may include one or more virtual machines running a virtual operating system, or other computing architecture involving virtualization (e.g., one or more flexible pools of logical storage that may be virtualized to maintain virtual storage for the server). In various embodiments, the server 120 may run one or more services or software applications that provide the functionality described below.

The computing units in server 120 may run one or more operating systems including any of the operating systems described above, as well as any commercially available server operating systems. The server 120 can also run any of a variety of additional server applications and/or mid-tier applications, including HTTP servers, FTP servers, CGI servers, JAVA servers, database servers, and the like.

In some implementations, the server 120 can include one or more applications to analyze and consolidate data feeds and/or event updates received from users of the

client devices

101, 102, 103, 104, 105, and 106. Server 120 may also include one or more applications to display data feeds and/or real-time events via one or more display devices of

client devices

101, 102, 103, 104, 105, and 106.

In some embodiments, the server 120 may be a server of a distributed system, or a server incorporating a blockchain. The server 120 may also be a cloud server, or a smart cloud computing server or a smart cloud host with artificial intelligence technology. The cloud Server is a host product in a cloud computing service system, and is used for solving the defects of high management difficulty and weak service expansibility in the traditional physical host and Virtual Private Server (VPS) service.

The system 100 may also include one or more databases 130. In some embodiments, these databases may be used to store data and other information. For example, one or more of the databases 130 may be used to store information such as audio files and video files. The database 130 may reside in various locations. For example, the database used by the server 120 may be local to the server 120, or may be remote from the server 120 and may communicate with the server 120 via a network-based or dedicated connection. The database 130 may be of different types. In certain embodiments, the database used by the server 120 may be, for example, a relational database. One or more of these databases may store, update, and retrieve data to and from the databases in response to the commands.

In some embodiments, one or more of the databases 130 may also be used by applications to store application data. The databases used by the application may be different types of databases, such as key-value stores, object stores, or conventional stores supported by a file system.

The system 100 of fig. 1 may be configured and operated in various ways to enable application of the various methods and apparatus described in accordance with the present disclosure.

Fig. 2 shows a flowchart of an electronic map-based information recommendation method 200 according to an exemplary embodiment of the present disclosure. As shown in fig. 2, the method 200 includes:

step S201, obtaining current position information of a target user and input travel destination information;

step S202, determining a travel type of the target user based on the current position information and travel destination information of the target user, wherein the travel type comprises allopatric travel; and

step S203, determining recommendation strategy information at least based on the travel type of the target user, wherein the recommendation strategy information comprises travel mode information and interest point information which are used for recommending the target user.

The applicant notices that the electronic map application program can be used for recommending and displaying travel mode information in a certain city for a user, and cannot recommend the travel mode information for the user when the user is going out across cities, in the method 200, the travel type of the user can be accurately identified by using the current position of the user and the input travel destination, the travel type can be identified by identifying users going out in different places, and then the contents such as the travel mode information and the interest point information can be pertinently recommended on the basis of the information contents acquired by using the electronic map application program, and the user experience can be improved.

Illustratively, the travel mode information may include cost information, required duration information, and the like of various travel modes, the travel modes may include local travel modes such as buses, subways, taxi trips, and the like, and may also include remote travel modes such as airplanes, trains, and the like, and the point-of-interest information may include names, business time information, location information, and the like of various points of interest. In some examples, the recommendation policy information may also include other content, such as travel service information included in the electronic map application, service information related to the point of interest, and the like. The travel service information may include ticketing service information of various travel modes, and the like, and the service information related to the point of interest may include accommodation reservation service information, dining reservation service information, and the like, for example. By identifying the travel type of the user and recommending the user in a targeted manner, the recommended content can better meet the requirements of the user, and the user experience is improved while the recommendation accuracy is improved.

On the basis of determining the information content for recommending to the target user, the specific recommendation manner may be set according to actual needs, for example, the recommendation may be performed in the form of a pop-up window, a push message, and the like, which is not limited herein.

For example, the obtaining of the current location information of the target user in step S201 may be achieved by obtaining the positioning information of the terminal of the user, or may be input or selected by the user, which is not limited herein. In some examples, a user may input a search request or a navigation request when using an electronic map application, and a travel destination of the user may be determined by obtaining search destination information included in the search request or navigation destination information included in the navigation request.

According to some embodiments, the determining of the travel type of the target user based on the current location information and the travel destination information of the target user in step S202 includes: and determining that the travel type of the target user is allopatric travel in response to that the current position and the travel destination of the target user are in different cities. Therefore, the method can simply, rapidly and accurately determine the users going out from different places, and carry out targeted recommendation based on the users going out from different places.

For example, the travel type of the target user may be determined in other manners. For example, after a user inputs a navigation request, information of a navigation origin and a navigation destination is acquired, and in response to that the navigation origin and the navigation destination are in different cities, the travel type of the user is determined to be allopatric travel.

Illustratively, the travel type of the target user may also include other types. For example, it may be determined that the travel type of the target user is local travel in response to that the current location and the travel destination of the target user are in the same city. For another example, the travel type of the target user may be determined to be cross-country travel in response to that the current location and the travel destination of the target user are in different countries. It should be understood that the user's travel types may be divided according to travel distance, or divided according to changes of different levels of administrative divisions to which the departure place and the destination belong, or further divided more finely for different dimensions by being combined, which is not limited by the present disclosure.

According to some embodiments, the determining recommendation policy information based on at least the travel type of the target user in step S203 includes: obtaining historical search record information of a plurality of related users aiming at a plurality of interest points, wherein the travel types of each related user in the plurality of related users are the same as those of the target user; and determining recommendation strategy information based on the historical search record information of the plurality of related users. Therefore, the information which better meets the requirements of the target user can be determined and recommended by mining the historical search records of the users with the same trip types as the target user, and the recommendation accuracy is effectively improved.

For example, the multiple points of interest respectively correspond to different point of interest types, in this case, the target point of interest type for the target user may be determined based on historical search record information of multiple points of interest for the multiple related users, and the recommendation policy information may be determined based on the target point of interest type. The interest point types can be divided according to the user requirements, and can comprise types of accommodation, catering, shopping and the like. In some examples, the number of times of searching for each type of interest point by the multiple related users may be determined based on historical search record information of the multiple related users for the multiple interest points, and then the interest point type with the highest number of times of searching may be determined as the target interest point type for the target user, so that a corresponding recommendation policy may be determined to recommend the interest point information corresponding to the target interest point type to the target user. For example, in a case that the travel type of the target user is a displaced travel, in response to determining that the number of searches for accommodation interest points by the plurality of relevant users is the largest, determining a corresponding recommendation policy to recommend the accommodation interest points to the target user.

In some examples, the travel destination of each of the plurality of relevant users is the same as the travel destination of the target user, so that information for recommendation to the target user can be more accurately determined based on the search record information of the relevant user.

The applicant notices that during the course of a user going out by using the electronic map application program, the information content concerned by the user changes along with the change of the going stage. Based on this, according to some embodiments, the method 200 further comprises: obtaining travel plan information of the target user, wherein the travel plan information comprises travel time information; determining a current travel stage of the target user based on at least current time information and travel time information of the target user, and determining recommendation policy information based on at least a travel type of the target user in step S203 includes: and determining recommendation strategy information based on the travel type and the current travel stage of the target user. Therefore, when the user is in different travel stages, information can be recommended for the user in a targeted manner, the recommendation accuracy can be further improved, and the information acquisition efficiency of the user is improved.

Illustratively, the current travel stage may include types of pre-travel, mid-travel, post-travel, and the like, so that the user's needs in different travel stages can be recommended.

For example, the travel plan information may be input by the target user, or may be obtained by querying based on the information of the target user. For example, for a target user who travels in different places, the travel plan information of the target user can be obtained through a ticket booking service included in an electronic map application program or through a third-party ticket platform for inquiring ticket booking information of the target user.

Generally speaking, the travel stages of the users going out in different places comprise a different place travel stage crossing a city and a local travel stage going out in the same city, and on the basis, the travel stages of the users going out in different places can be further divided so as to more accurately mine the demands of the users. Based on this, according to some embodiments, the travel type of the target user is allopatric travel, and the current travel stage includes at least one of: the user is going to go to different places and is going to arrive at different places. Therefore, corresponding information can be recommended for the users who go out in different places in different phases, and the recommendation accuracy is improved.

Further, according to some embodiments, the determining the current travel stage of the target user based on at least the travel time information and the current time information of the target user comprises: and determining the current travel stage of the target user based on the current time information, the travel time information of the target user and the current position information. By combining the current position information of the target user, the current travel stage of the target user can be determined more accurately.

It should be understood that users going to different places usually need to finish the city-crossing trip by using airplanes, trains and the like, that is, before departing to different places, users going to different places need to go to transport hubs such as airports, railway stations and the like in the city. In this case, it is necessary to consider a time required for the user to go to the transportation junction from the current position to more accurately determine the corresponding travel stage information.

In this case, according to some embodiments, the travel plan information of the target user further includes remote travel departure place information and remote travel departure time information, and the determining the current travel stage of the target user based on the current time information, the travel plan information of the target user, and the current location information includes: determining local departure time of the target user based on the different-place trip departure time information, the different-place trip departure place information and the current position information of the target user; and determining that the current travel stage of the target user is to go to a different place for departure in response to the fact that the time interval between the current time and the local departure time is less than a first preset time length. Therefore, the current travel stage of the user who travels in different places can be simply, rapidly and accurately determined, and the recommendation accuracy can be further improved.

As described above, for a target user who travels in different places, the destination user can obtain the transportation hub location information (i.e., the information of the departure place and the departure time) and the information of the departure time corresponding to the different-place travel mode by querying the ticket booking information of the target user. Further, the navigation route planning service included in the electronic map application program can be used for predicting the time required by the target user to go to the transportation junction from the current position, so that the local departure time of the target user can be obtained. For example, the first preset time period may be set according to actual requirements, and is not limited thereto.

On this basis, according to some embodiments, when the current travel stage of the target user is to go to a different place, the recommendation policy information further includes local travel mode information recommended to the target user, and wherein the local travel mode information recommended to the target user is determined based on the different place travel origin information and the current location information of the target user. Therefore, corresponding local trip mode information can be recommended in a targeted manner according to the local trip demand that a target user needs to go to a different-place trip departure place, so that the demand of the user is fully met, and the user experience is improved.

For example, the local travel mode information may include cost information, required duration information, traffic information, road condition information, and the like corresponding to different travel modes (for example, modes of buses, subways, taxi hiring, and the like), and further, corresponding local departure time may be pushed to the user according to the required duration information corresponding to each travel mode and the different-place travel departure time information, so as to be referred by the user. In some examples, corresponding local travel service information may also be recommended to the target user, so as to improve the recommendation accuracy and conversion rate of the travel service.

Generally, when a user going out in different places finishes going out by using a cross-city public transportation mode such as an airplane, a train and the like, relevant information required by specific public transportation needs to be determined. For example, when the different-place trip mode is an airplane, the related information includes a flight number, a check-in counter, a gate, a seat number, airplane delay information, and the like, and when the different-place trip mode is a train, the related information includes a train number, a ticket gate, a platform, a seat number, train delay information, and the like.

Based on this, according to some embodiments, the travel plan information of the target user further includes information related to a different travel mode, and the determining recommendation policy information in step S203 based on the travel type and the current travel stage of the target user includes: and determining a recommendation strategy to recommend relevant information of the different-place travel mode to the user in response to the fact that the current travel stage of the target user is about to depart to a different place and the time interval between the current time and the different-place travel departure time is smaller than a second preset time length. Therefore, the requirements of the target user on the relevant information when the target user finishes the city-crossing trip by using the different-place trip mode can be recommended in a targeted manner, and the user experience is further improved.

The method can further consider the actual requirements of the target users when the target users arrive at different places for the target users going out at different places, and carries out recommendation in a targeted manner so as to fully meet the requirements of the users. According to some embodiments, the travel plan information of the target user further includes offsite travel arrival time information, and the determining the current travel stage of the target user based on the current time information and the travel plan information of the target user includes: and determining that the current travel stage of the target user is to arrive at a different place in response to that the time interval between the current time and the arrival time of the travel at the different place is less than a third preset time length. Therefore, the current travel stage of the user who travels in different places can be simply, rapidly and accurately determined, and the recommendation accuracy can be further improved.

As described above, users going out in different places usually need to finish the trip across cities by using airplanes, trains, etc., so the users going out in different places will arrive at the transportation hub such as the airport, train station, etc. of the city where the destination is located first, and then go to the trip destination from the transportation hub. In this case, the requirements that may exist when the user departs from the transportation junction need to be considered to make targeted recommendations.

According to some embodiments, the travel plan information of the target user further includes offsite travel arrival place information, and the determining of the recommendation strategy information in step S203 includes, based on the travel type and the current travel stage of the target user: in response to determining that the current travel stage of the target user is to arrive at a different place, determining relevant information of a different place travel arrival place based on the information of the different place travel arrival place; and determining a recommendation strategy to recommend the relevant information of the place of arrival of the different trip to the user. Therefore, targeted recommendation can be performed according to the information requirement of the target user after the target user arrives at a different place, and the user experience is further improved.

Illustratively, after responding to the determination that the target user is about to arrive at a different place, relevant information can be inquired about the different place for the arrival of the trip. The relevant information of the different place trip arrival place can comprise different place current weather information, corresponding public transportation station information of the different place trip arrival place, public transportation line information and the like. In some examples, when the travel destination of the user is determined, information of a travel mode from the place of arrival to the travel destination can be recommended for the user, so as to further meet the requirement of the user.

Fig. 3 shows a flowchart of an electronic map-based information recommendation method 300 according to an exemplary embodiment of the present disclosure. In this embodiment, the travel type of the target user includes displaced travel, as shown in fig. 3, the method 300 includes:

step S301, acquiring current position information of a target user and input travel destination information;

step S302, responding to the situation that the current position and the travel destination of the target user are in different cities, and determining that the travel type of the target user is allopatric travel;

step S303, obtaining travel plan information of the target user, wherein the travel plan information comprises travel time information;

step S304, determining the current travel stage of the target user at least based on the current time information and the travel time information of the target user;

step S305, determining recommendation strategy information based on the travel type and the current travel stage of the target user.

Therefore, whether the user is a different-place trip user can be accurately identified by utilizing the current position information and the trip destination of the user, and then the current trip stage of the user is identified based on the current time information and the trip plan information of the user, so that the information can be pertinently recommended to the user when the user is in different trip stages, the recommendation accuracy can be further improved, the information acquisition efficiency of the user is improved, and the user experience is improved.

In the technical scheme of the disclosure, the collection, storage, use, processing, transmission, provision, disclosure and other processing of the personal information of the related user are all in accordance with the regulations of related laws and regulations and do not violate the good customs of the public order.

According to another aspect of the present disclosure, an electronic map-based information recommendation apparatus is also provided. Fig. 4 illustrates a block diagram of a structure of an electronic map-based information recommendation apparatus 400 according to an exemplary embodiment of the present disclosure. As shown in fig. 4, the apparatus 400 includes:

an acquisition unit 401 configured to acquire current location information of a target user and input travel destination information;

a first determining unit 402 configured to determine a travel type of the target user based on current location information and travel destination information of the target user, the travel type including a displaced travel; and

a second determining unit 403, configured to determine recommendation policy information based on at least the travel type of the target user, where the recommendation policy information includes travel mode information and point of interest information for recommending to the target user.

The operations of the units 401 to 403 of the electronic map based information recommendation device 400 are similar to the operations of the steps S201 to S203 described above, and are not repeated herein.

According to another aspect of the present disclosure, there is also provided an electronic device including: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the information recommendation method described above.

According to another aspect of the present disclosure, there is also provided a non-transitory computer-readable storage medium storing computer instructions for causing the computer to perform the above-described information recommendation method.

According to another aspect of the present disclosure, there is also provided a computer program product comprising a computer program, wherein the computer program when executed by a processor implements the information recommendation method described above.

Referring to fig. 5, a block diagram of a structure of an electronic device 500, which may be a server or a client of the present disclosure, which is an example of a hardware device that may be applied to aspects of the present disclosure, will now be described. Electronic device is intended to represent various forms of digital electronic computer devices, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. Electronic devices may also represent various forms of mobile devices, such as personal digital processors, cellular telephones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not intended to limit implementations of the disclosure described and/or claimed herein.

As shown in fig. 5, the device 500 comprises a computing unit 501 which may perform various suitable actions and processes according to a computer program stored in a Read Only Memory (ROM) 502 or a computer program loaded from a storage unit 508 into a Random Access Memory (RAM) 503. In the RAM 503, various programs and data required for the operation of the device 500 can also be stored. The calculation unit 501, the ROM 502, and the RAM 503 are connected to each other by a bus 504. An input/output (I/O) interface 505 is also connected to bus 504.

A number of components in the device 500 are connected to the I/O interface 505, including: an input unit 506, an output unit 507, a storage unit 508, and a communication unit 509. The input unit 506 may be any type of device capable of inputting information to the device 500, and the input unit 506 may receive input numeric or character information and generate key signal inputs related to user settings and/or function controls of the electronic device, and may include, but is not limited to, a mouse, a keyboard, a touch screen, a track pad, a track ball, a joystick, a microphone, and/or a remote controller. Output unit 507 may be any type of device capable of presenting information and may include, but is not limited to, a display, speakers, a video/audio output terminal, a vibrator, and/or a printer. The storage unit 508 may include, but is not limited to, a magnetic disk, an optical disk. The communication unit 509 allows the device 500 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunications networks, and may include, but is not limited to, modems, network cards, infrared communication devices, wireless communication transceivers and/or chipsets, such as bluetooth (TM) devices, 802.11 devices, wiFi devices, wiMax devices, cellular communication devices, and/or the like.

The computing unit 501 may be a variety of general and/or special purpose processing components with processing and computing capabilities. Some examples of the computing unit 501 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various dedicated Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, and so forth. The calculation unit 501 executes the respective methods and processes described above, such as the information recommendation method. For example, in some embodiments, the information recommendation method may be implemented as a computer software program tangibly embodied on a machine-readable medium, such as storage unit 508. In some embodiments, part or all of the computer program may be loaded and/or installed onto the device 500 via the ROM 502 and/or the communication unit 509. When the computer program is loaded into the RAM 503 and executed by the computing unit 501, one or more steps of the information recommendation method described above may be performed. Alternatively, in other embodiments, the computing unit 501 may be configured to perform the information recommendation method in any other suitable manner (e.g., by means of firmware).

Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), system on a chip (SOCs), complex Programmable Logic Devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.

Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.

In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.

The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), the internet, and blockchain networks.

The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server may be a cloud server, a server of a distributed system, or a server combining a blockchain.

It should be understood that various forms of the flows shown above, reordering, adding or deleting steps, may be used. For example, the steps described in the present disclosure may be performed in parallel, sequentially or in different orders, and are not limited herein as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved.

Although embodiments or examples of the present disclosure have been described with reference to the accompanying drawings, it is to be understood that the above-described methods, systems and apparatus are merely exemplary embodiments or examples and that the scope of the present invention is not limited by these embodiments or examples, but only by the claims as issued and their equivalents. Various elements in the embodiments or examples may be omitted or may be replaced with equivalents thereof. Further, the steps may be performed in an order different from that described in the present disclosure. Further, various elements in the embodiments or examples may be combined in various ways. It is important that as technology evolves, many of the elements described herein may be replaced with equivalent elements that appear after the present disclosure.

Claims

1. An information recommendation method based on an electronic map comprises the following steps:

acquiring current position information of a target user and input travel destination information;

determining a travel type of the target user based on the current position information and travel destination information of the target user, wherein the travel type comprises allopatric travel;

and determining recommendation strategy information at least based on the travel type of the target user, wherein the recommendation strategy information comprises travel mode information and interest point information which are used for recommending the target user.

2. The method of claim 1, wherein the determining of the travel type of the target user based on the current location information and travel destination information of the target user comprises:

and determining that the travel type of the target user is allopatric travel in response to that the current position and the travel destination of the target user are in different cities.

3. The method of claim 1 or 2, wherein the determining recommendation policy information based at least on the travel type of the target user comprises:

obtaining historical search record information of a plurality of related users aiming at a plurality of interest points, wherein the travel types of each related user in the plurality of related users are the same as those of the target user; and

and determining recommendation strategy information based on the historical search record information of the plurality of related users.

4. The method of any of claims 1-3, further comprising:

obtaining travel plan information of the target user, wherein the travel plan information comprises travel time information;

determining a current travel stage of the target user based on at least current time information and travel time information of the target user,

and wherein the determining recommendation policy information based at least on the travel type of the target user comprises:

and determining recommendation strategy information based on the travel type and the current travel stage of the target user.

5. The method of claim 4, wherein the target user's travel type is offsite travel, the current travel stage comprising at least one of:

the user is going to go to different places and is going to arrive at different places.

6. The method of claim 5, wherein said determining a current travel stage of the target user based on at least the travel time information and the current time information of the target user comprises:

and determining the current travel stage of the target user based on the current time information, the travel time information of the target user and the current position information.

7. The method of claim 6, wherein the travel plan information of the target user further includes offsite travel origin information and offsite travel departure time information, and the determining the current travel stage of the target user based on the current time information, the travel plan information of the target user, and the current location information comprises:

determining local departure time of the target user based on the different-place trip departure time information, the different-place trip departure place information and the current position information of the target user;

and determining that the current travel stage of the target user is to go to a different place for departure in response to the fact that the time interval between the current time and the local departure time is less than a first preset time length.

8. The method of claim 7, wherein, when the current travel stage of the target user is to go to a different place for departure, the recommendation policy information further includes local travel mode information for recommending to the target user,

and determining local travel mode information for recommending to the target user based on the different travel origin information and the current position information of the target user.

9. The method of claim 7, wherein the travel plan information of the target user further includes information related to a displaced travel mode, and wherein, when the determining of the recommendation strategy information based on the travel type and the current travel stage of the target user includes:

and in response to the fact that the current travel stage of the target user is determined to be about to go to a different place, and the time interval between the current time and the different place travel departure time is determined to be less than a second preset time, determining a recommendation strategy so as to recommend relevant information of the different place travel mode to the user.

10. The method of claim 5, wherein the target user's travel plan information further comprises displaced travel arrival time information, and the determining the target user's current travel stage based on the current time information and the target user's travel plan information comprises:

and determining that the current travel stage of the target user is to arrive at a different place in response to that the time interval between the current time and the arrival time of the travel at the different place is less than a third preset time length.

11. The method of claim 10, wherein the travel plan information of the target user further includes offsite travel arrival information, and wherein the determining recommended strategy information based on the travel type and the current travel stage of the target user comprises:

in response to the fact that the current travel stage of the target user is to arrive at a different place, relevant information of a different place travel arrival place is determined based on the information of the different place travel arrival place; and

and determining a recommendation strategy to recommend the relevant information of the allopatric travel arrival place to the user.

12. An electronic map-based information recommendation apparatus comprising:

an acquisition unit configured to acquire current location information of a target user and input travel destination information;

a first determining unit configured to determine a travel type of the target user based on current location information and travel destination information of the target user, the travel type including allopatric travel;

a second determining unit configured to determine recommendation policy information based on at least the travel type of the target user, the recommendation policy information including travel mode information and point of interest information for recommending to the target user.

13. An electronic device, comprising:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein

The memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-11.

14. A non-transitory computer readable storage medium having stored thereon computer instructions for causing a computer to perform the method of any one of claims 1-11.

15. A computer program product comprising a computer program, wherein the computer program realizes the method according to any of claims 1-11 when executed by a processor.