CN111143676A - Interest point recommendation method and device, electronic equipment and computer-readable storage medium - Google Patents
Interest point recommendation method and device, electronic equipment and computer-readable storage medium Download PDFInfo
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- G06F16/95—Retrieval from the web
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- G06F16/9535—Search customisation based on user profiles and personalisation
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- G06F16/90—Details of database functions independent of the retrieved data types
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Abstract
The invention provides an interest point recommendation method, an interest point recommendation device, electronic equipment and a computer-readable storage medium, wherein the interest point recommendation method comprises the following steps: step S1, obtaining the destination position of the current user; step S2, determining interest points to be recommended within a preset distance range from the destination position; and step S3, recommending the current user based on the interest points to be recommended. According to the interest point recommendation method, unknown but possibly interested places around the position of the user can be recommended, and convenience is brought to the user for going out.
Description
Technical Field
The invention relates to the field of vehicles, in particular to a point of interest recommendation method and device, electronic equipment and a computer-readable storage medium.
Background
In a centralized location (e.g. a residential district), there are usually many POIs (Point of interest, representing a location on a map) around its vicinity, and each POI may contain 4 pieces of information, such as name, category, coordinates, classification, etc., and the location is, for example, shopping, entertainment, scenic spot, etc. The POI locations in the walking range are generally known to the residents of the position, but the POI locations in a certain journey (e.g., within 3 km or 5 km) are not necessarily known to the residents of the position. When a user drives a car to go out, how to recommend places which are unknown at the periphery but may be interested to the user is a problem to be solved.
Disclosure of Invention
In view of this, the invention provides a method and an apparatus for recommending points of interest, an electronic device, and a computer-readable storage medium, which can recommend places around a location where a user is located but which are unknown but may be interested, and provide convenience for the user to go out.
In order to solve the above technical problem, in one aspect, the present invention provides a method for recommending a point of interest, including the steps of:
step S1, obtaining the destination position of the current user;
step S2, determining interest points to be recommended within a preset distance range from the destination position;
and step S3, recommending the current user based on the interest points to be recommended.
Further, the step S2 includes:
step S21, determining an area within a predetermined distance range from the destination position;
and step S22, in the area, determining the interest points with the visited frequency exceeding a predetermined value as the interest points to be recommended.
Further, the step S2 further includes:
step S23, determining the relevant users who visit the interest points to be recommended;
step S24, analyzing historical travel data of the related user and the current user, and determining travel similarity of the related user and the current user according to the historical travel data of the related user and the current user;
step S25, screening the to-be-recommended interest points based on the travel similarity, so as to remove the interest points visited by the relevant users whose travel similarity is lower than a predetermined value.
Further, in the step S3, recommendation is performed based on the filtered interest points to be recommended.
Further, the step S3 includes:
comparing the screened interest points with historical travel data of the current user;
and removing the interest points which have been already passed by the current user, and recommending the remaining interest points to the current user.
Further, the step S3 includes:
comparing the screened interest points with historical travel data of the current user;
and reserving the interest points which are repeatedly traveled by the current user and the interest points which are not traveled by the current user, and recommending the reserved interest points.
In a second aspect, the present invention provides a point of interest recommendation apparatus, including:
the position confirmation module is used for acquiring the destination position of the current user;
the interest point acquisition module is used for determining interest points to be recommended within a preset distance range from the destination position;
and the recommending module is used for recommending the current user based on the interest points to be recommended.
Further, the interest point obtaining module includes:
the area determining module is used for determining an area within a preset distance range from the destination position;
and the interest point to be recommended determining module is used for determining the interest points with the visited frequency exceeding a preset value in the area as the interest points to be recommended.
Further, the interest point obtaining module further includes:
the relevant user determining module is used for determining relevant users accessing the interest points to be recommended;
the similarity calculation module is used for analyzing historical travel data of the related user and the current user and determining travel similarity of the related user and the current user according to the historical travel data of the related user and the current user;
and the screening module is used for screening the interest points to be recommended based on the travel similarity so as to remove the interest points accessed by the related users with the similarity lower than a preset value.
Further, the recommending module recommends based on the filtered interest points to be recommended.
Further, the recommendation module is to:
comparing the screened interest points with historical travel data of the current user;
and removing the interest points which have been already passed by the current user, and recommending the remaining interest points to the current user.
Further, the recommendation module is to:
comparing the screened interest points with historical travel data of the current user;
and reserving the interest points which are repeatedly traveled by the current user and the interest points which are not traveled by the current user, and recommending the reserved interest points.
In a third aspect, the present invention provides an electronic device for point of interest recommendation, comprising:
one or more processors;
one or more memories having computer readable code stored therein, which when executed by the one or more processors, causes the processors to perform the steps of:
step S1, obtaining the destination position of the current user;
step S2, determining interest points to be recommended within a preset distance range from the destination position;
and step S3, recommending the current user based on the interest points to be recommended.
In a fourth aspect, the present invention provides a computer readable storage medium having computer readable code stored therein, which when executed by one or more processors, causes the processors to perform the steps of:
step S1, obtaining the destination position of the current user;
step S2, determining interest points to be recommended within a preset distance range from the destination position;
and step S3, recommending the current user based on the interest points to be recommended.
The technical scheme of the invention at least has one of the following beneficial effects:
according to the interest point recommendation method, the current user is recommended based on the interest points in the preset distance range of the destination position, so that the travel convenience of the current user can be increased;
further, the interest points visited by the relevant users with the historical travel data similarity lower than the preset value with the current user are removed, and users with the travel similarity higher than the preset value (namely users with close interests) can be recommended to frequently go (or go) to obtain the interest points with higher value;
furthermore, the interest points which have been already passed by the current user are removed, only the interest points which have not been passed by the current user are recommended, the reserved interest points are recommended, the unknown places or the unknown interest points of the current user can be recommended, and the practical value of the interest points is increased;
furthermore, for the interest points accessed by the users close to the interest and hobbies of the current user, after the interest points which the current user has ever visited are removed, the rest interest points are further screened, and the interest points close to the interest of the current user are reserved for recommendation, so that the recommended interest points can be further matched with the travel habits of the current user.
Drawings
FIG. 1 is a flow chart of a point of interest recommendation method according to an embodiment of the invention;
FIG. 2 is a schematic diagram of a point of interest recommendation apparatus according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of an electronic device for point of interest recommendation according to an embodiment of the present invention.
Detailed Description
The following detailed description of embodiments of the present invention will be made with reference to the accompanying drawings and examples. The following examples are intended to illustrate the invention but are not intended to limit the scope of the invention.
In a centralized location (e.g., a residential district), there are usually many POI (Point of interest) locations around its vicinity, such as shopping, entertainment, scenic spots, etc. The POI locations in the walking range are generally known to the residents of the position, but the POI locations in a certain journey (e.g., within 3 km or 5 km) are not necessarily known to the residents of the position. When a user drives a car to go out, how to recommend places which are unknown at the periphery but may be interested to the user is a problem to be solved.
Based on the method, the system and the device, the POI places which are possibly interested in the surroundings are recommended for the user who drives to go out based on the internet automobile, the user navigation travel track and the like. And (4) finding POI (point of interest) around the hot destination by analyzing a large number of user travel tracks at the same position, and then recommending the POI to the user.
The method and the system recommend the interest points to the periphery of the user position, and the interest points may not be interesting to the user (the user can directly ignore) or may be interesting (the user obtains the new place recommendation).
For example, a restaurant which is very popular is newly opened by 5km from the a cell, many other vehicles in the a cell are gathered frequently, and the cloud server (cloud end) provides information to the vehicle end which wants to drive to XX in the a cell, so that XX can drive to the restaurant popular to taste.
First, a point of interest recommendation method according to an embodiment of the present invention is described with reference to fig. 1.
As shown in fig. 1, the method for recommending a point of interest according to an embodiment of the present invention includes:
in step S1, the destination location of the current user is acquired.
Optionally, based on an internet car navigator, a user travel track (longitude and latitude coordinates) is collected in real time, and the track position is transmitted to a cloud server end (cloud end) through a wireless network for storage, and the cloud end determines the destination position of the current user based on the travel track.
Further, the destination location may include, for example, a residence, a work company location, a travel destination, and so forth.
And step S2, determining the interest points to be recommended within a preset distance range from the destination position.
According to some embodiments of the invention, step S2 includes:
in step S21, an area within a predetermined distance from the destination position is determined.
Alternatively, the predetermined distance range is a peripheral region of the destination, in other words, a region at a relatively short distance from the destination. Therefore, the situations of inconvenience and high cost of traveling of the user due to too far distance can be avoided.
Further, the predetermined distance range may also be set based on the user travel route, for example, a place closer to the historical travel route (e.g., a place closer to the commute route).
Step S22, in the region, determining the interest points with the visited frequency exceeding a predetermined value as the interest points to be recommended.
Alternatively, the vehicle visiting the point of interest (POI) may be any vehicle traveling, that is, any point of interest having a vehicle visiting frequency exceeding a predetermined value may be taken as the point of interest to be recommended.
For example, setting the predetermined value to be 50, and setting the point of interest to be an XX restaurant at a distance of 5KM from the a cell, when any traveling vehicle visits the XX restaurant more than 50 times, the XX restaurant serves as the point of interest to be recommended.
Further, step S2 further includes:
and step S23, determining the relevant users who access the interest points to be recommended.
That is, relevant users who access the interest point to be recommended are identified, so that better recommendation is facilitated.
Step S24, analyzing historical travel data of the relevant user and the current user, and determining travel similarity between the relevant user and the current user according to the historical travel data of the relevant user and the current user.
Optionally, historical travel road section data or destination data of the relevant user and the current user are analyzed, and travel similarity between the relevant user and the current user is determined according to the historical travel road section or the destination of the relevant user and the current user.
Step S25, screening the to-be-recommended interest points based on the travel similarity, so as to remove the interest points visited by the relevant users whose travel similarity is lower than a predetermined value.
That is, the recommendation is performed after the user visiting the interest points with different frequently visited interest points (i.e. the travel similarity is lower than the predetermined value) is filtered out. Therefore, the method can be better matched with the interests and hobbies of the current user, and the purpose is stronger.
Alternatively, points of interest visited by users whose destination or travel section similarity is lower than a predetermined value may be removed.
For example, points of interest visited by relevant users whose destination similarity is lower than a predetermined value are removed. Thus, points of interest frequented (or frequented) by other users may be recommended based on destinations having a similarity higher than a predetermined value, in other words, points of interest frequented (or frequented) by users (such as neighbors or the like) near the residence (home or temporary residence) or users (such as coworkers or the like) near the company may be recommended.
For example, the interest points visited by the relevant users whose travel section similarity is lower than a predetermined value are removed. Therefore, the points of interest that other users have frequented (or visited) can be recommended based on the travel section with the similarity higher than the preset value, in other words, the points of interest that users along the road (such as users passing the same section during work) can be recommended to frequented (or visited).
And step S3, recommending the current user based on the interest points to be recommended.
That is, frequent (or past) interest points of other users whose travel similarity is higher than a predetermined value may be recommended for the user to select.
According to some embodiments of the invention, step S3 includes:
1) comparing the screened interest points with historical travel data of the current user;
2) and reserving the interest points which have not been visited by the current user, and recommending the reserved interest points.
Therefore, places unknown by the current user or interest points which have not been visited by the current user can be recommended, namely, the current user does not continue to recommend after going to the recommended places, and the main purpose is to help the user to find a new place, so that the interest points which have been visited by the current user are prevented from being recommended, and the interest points which have no practical value are avoided. Meanwhile, the interest points which are used for traveling for many times at present can be recommended to other users, so that the other users can conveniently obtain the appropriate interest points.
Furthermore, the similarity between the remaining interest points and the interest points which have been taken out by the current user for many times can be determined, and the interest points of which the similarity meets the preset condition are recommended.
That is, in the remaining interest points, the current user's own interest is further considered, and purposeful recommendation is made based on the current user's interest.
In view of the above, as a preferable mode, for example: firstly, finding out peripheral interest points, then determining interest points with higher visited frequency in the peripheral interest points, then analyzing the similarity between the crowd frequently removing the interest points and the interest and taste of the current user, then removing the interest points which are removed by the current user, and finally further analyzing the interest points which are matched with the interest and taste of the current user in the rest interest points and recommending the interest points to the current user. Therefore, through layer-by-layer analysis and screening, recommendation can be carried out in a more targeted manner, the probability of going out based on recommendation is higher, and user experience is better.
In the following, referring to fig. 2, a point of interest recommendation apparatus 1000 according to an embodiment of the present invention is described.
As shown in fig. 2, an interest point recommending apparatus 1000 according to an embodiment of the present invention includes:
a location confirmation module 1001 configured to obtain a destination location of a current user;
an interest point obtaining module 1002, configured to determine an interest point to be recommended within a predetermined distance range from a destination location;
further, the interest point obtaining module comprises:
an area determining module 10021, configured to determine an area within a predetermined distance range from the destination location;
a to-be-recommended interest point determining module 10022, configured to determine, in the area, an interest point whose visited frequency exceeds a predetermined value as the to-be-recommended interest point.
Further, the interest point obtaining module further includes:
a relevant user determining module 10023, configured to determine a relevant user who accesses the point of interest to be recommended;
the similarity calculation module 10024 is configured to analyze historical travel data of the relevant user and the current user, and determine the travel similarity between the relevant user and the current user according to the historical travel data of the relevant user and the current user;
the screening module 10025 is configured to screen the to-be-recommended interest points based on the travel similarity to remove the interest points visited by the relevant users whose similarity is lower than the predetermined value.
The recommending module 1003 is configured to recommend the current user based on the interest point to be recommended.
Further, the recommending module 1003 recommends based on the filtered interest points to be recommended.
Further, the recommending module 1003 is used for:
comparing the screened interest points with historical travel data of the current user;
and removing the interest points which have been already passed by the current user, and recommending the remaining interest points to the current user.
Further, the recommending module 1003 is used for:
comparing the screened interest points with historical travel data of the current user;
and reserving the interest points which are repeatedly traveled by the current user and the interest points which are not traveled by the current user, and recommending the reserved interest points.
Further, the point of interest recommending apparatus 1000 may also be respectively used for corresponding steps in the point of interest recommending method, and a detailed description thereof is omitted here.
In addition, an electronic device for point of interest recommendation according to an embodiment of the present invention is described with reference to fig. 3.
As shown in fig. 3, an electronic device for point of interest recommendation according to an embodiment of the present invention includes:
a processor 1401 and a memory 1402, in which memory 1402 computer program instructions are stored, wherein the computer program instructions, when executed by the processor, cause the processor 1401 to perform the steps of:
step S1, obtaining the destination position of the current user;
step S2, determining interest points to be recommended within a preset distance range from the destination position;
and step S3, recommending the current user based on the interest points to be recommended.
Further, the processor 1401 may also perform corresponding steps in the point of interest recommendation method, and a detailed description thereof is omitted herein.
The various interfaces and devices described above may be interconnected by a bus architecture. A bus architecture may be any architecture that may include any number of interconnected buses and bridges. Various circuits of one or more Central Processing Units (CPUs), represented in particular by processor 1401, and one or more memories, represented by memory 1402, are coupled together. The bus architecture may also connect various other circuits such as peripherals, voltage regulators, power management circuits, and the like. It will be appreciated that a bus architecture is used to enable communications among the components. The bus architecture includes a power bus, a control bus, and a status signal bus, in addition to a data bus, all of which are well known in the art and therefore will not be described in detail herein.
The network interface 1403 may be connected to a network (e.g., the internet, a local area network, etc.), obtain relevant data from the network, and store the relevant data in the hard disk 1405.
The input device 1404 may receive various instructions from an operator and send them to the processor 1401 for execution. The input device 1404 may include a keyboard or a pointing device (e.g., a mouse, trackball, touch pad, or touch screen, among others.
The display device 1406 may display a result obtained by the processor 1401 executing the instruction.
The memory 1402 is used for storing programs and data necessary for operating the operating system, and data such as intermediate results in the calculation process of the processor 1401.
It will be appreciated that the memory 1402 in embodiments of the invention may be either volatile memory or nonvolatile memory, or may include both volatile and nonvolatile memory. The nonvolatile memory may be a Read Only Memory (ROM), a Programmable Read Only Memory (PROM), an Erasable Programmable Read Only Memory (EPROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), or a flash memory. Volatile memory can be Random Access Memory (RAM), which acts as external cache memory. The memory 1402 of the apparatus and methods described herein is intended to comprise, without being limited to, these and any other suitable types of memory.
In some embodiments, memory 1402 stores elements, executable modules or data structures, or a subset thereof, or an expanded set thereof as follows: an operating system 14021 and application programs 14014.
The operating system 14021 includes various system programs, such as a framework layer, a core library layer, a driver layer, and the like, for implementing various basic services and processing hardware-based tasks. The application 14014 includes various applications, such as a Browser (Browser), and the like, for implementing various application services. A program implementing a method according to an embodiment of the invention may be included in the application 14014.
The processor 1401 first XXXX is used when calling and executing the application program and data stored in the memory 1402, specifically, the program or the instructions stored in the application 14014.
The methods disclosed by the above-described embodiments of the present invention may be applied to the processor 1401, or may be implemented by the processor 1401. Processor 1401 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by instructions in the form of hardware integrated logic circuits or software in the processor 1401. The processor 1401 may be a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, and may implement or perform the methods, steps, and logic blocks disclosed in embodiments of the present invention. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory 1402, and a processor 1401 reads information in the memory 1402 and performs the steps of the above method in combination with hardware thereof.
It is to be understood that the embodiments described herein may be implemented in hardware, software, firmware, middleware, microcode, or any combination thereof. For a hardware implementation, the processing units may be implemented within one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), general purpose processors, controllers, micro-controllers, microprocessors, other electronic units designed to perform the functions described herein, or a combination thereof.
For a software implementation, the techniques described herein may be implemented with modules (e.g., procedures, functions, and so on) that perform the functions described herein. The software codes may be stored in a memory and executed by a processor. The memory may be implemented within the processor or external to the processor.
In addition, an embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the processor is caused to execute the following steps:
step S1, obtaining the destination position of the current user;
step S2, determining interest points to be recommended within a preset distance range from the destination position;
and step S3, recommending the current user based on the interest points to be recommended.
Further, the processor may also perform corresponding steps in the point of interest recommendation method, and a detailed description thereof is omitted herein.
Still further, the present invention also provides a program product comprising execution instructions stored in a readable storage medium. The at least one processor of the electronic device (which may be, for example, a server, a cloud server, or a part of a server, etc.) may read the execution instruction from the readable storage medium, and execute the execution instruction, so that the point of interest recommendation apparatus 1000 implements the point of interest recommendation method provided in the foregoing various embodiments.
In the several embodiments provided in the present application, it should be understood that the disclosed method and apparatus may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, 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 through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be physically included alone, or two or more units may be integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
The integrated unit implemented in the form of a software functional unit may be stored in a computer readable storage medium. The software functional unit is stored in a storage medium and includes several instructions to enable a computer device (which may be a personal computer, a server, or a network device) to execute some steps of the transceiving method according to various embodiments of the present invention. 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.
While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (14)
1. A point of interest recommendation method is characterized by comprising the following steps:
step S1, obtaining the destination position of the current user;
step S2, determining interest points to be recommended within a preset distance range from the destination position;
and step S3, recommending the current user based on the interest points to be recommended.
2. The method of recommending a point of interest according to claim 1, wherein said step S2 includes:
step S21, determining an area within a predetermined distance range from the destination position;
and step S22, in the area, determining the interest points with the visited frequency exceeding a predetermined value as the interest points to be recommended.
3. The method of recommending a point of interest according to claim 2, wherein said step S2 further comprises:
step S23, determining the relevant users who visit the interest points to be recommended;
step S24, analyzing historical travel data of the related user and the current user, and determining travel similarity of the related user and the current user according to the historical travel data of the related user and the current user;
step S25, screening the to-be-recommended interest points based on the travel similarity, so as to remove the interest points visited by the relevant users whose travel similarity is lower than a predetermined value.
4. The method of recommending point of interest according to claim 3, wherein in said step S3, recommendation is made based on the filtered points of interest to be recommended.
5. The method of recommending a point of interest according to claim 4, wherein said step S3 includes:
comparing the screened interest points with historical travel data of the current user;
and removing the interest points which have been already passed by the current user, and recommending the remaining interest points to the current user.
6. The method of claim 5, wherein for the remaining points of interest, similarity between the remaining points of interest and points of interest that have been taken many times by the current user is determined, and points of interest with similarity satisfying a preset condition are recommended.
7. An apparatus for point of interest recommendation, comprising:
the position confirmation module is used for acquiring the destination position of the current user;
the interest point acquisition module is used for determining interest points to be recommended within a preset distance range from the destination position;
and the recommending module is used for recommending the current user based on the interest points to be recommended.
8. The device of claim 1, wherein the point of interest obtaining module comprises:
the area determining module is used for determining an area within a preset distance range from the destination position;
and the interest point to be recommended determining module is used for determining the interest points with the visited frequency exceeding a preset value in the area as the interest points to be recommended.
9. The device of claim 8, wherein the point of interest obtaining module further comprises:
the relevant user determining module is used for determining relevant users accessing the interest points to be recommended;
the similarity calculation module is used for analyzing historical travel data of the related user and the current user and determining travel similarity of the related user and the current user according to the historical travel data of the related user and the current user;
and the screening module is used for screening the interest points to be recommended based on the travel similarity so as to remove the interest points accessed by the related users with the similarity lower than a preset value.
10. The point-of-interest recommendation device of claim 9, wherein the recommendation module recommends based on the filtered points of interest to be recommended.
11. The point-of-interest recommendation apparatus of claim 9, wherein the recommendation module is configured to:
comparing the screened interest points with historical travel data of the current user;
and removing the interest points which have been already passed by the current user, and recommending the remaining interest points to the current user.
12. The point-of-interest recommendation apparatus of claim 9, wherein the recommendation module is configured to:
comparing the screened interest points with historical travel data of the current user;
and reserving the interest points which are repeatedly traveled by the current user and the interest points which are not traveled by the current user, and recommending the reserved interest points.
13. An electronic device for point of interest recommendation, comprising:
one or more processors;
one or more memories having computer readable code stored therein, which when executed by the one or more processors, causes the processors to perform the steps of:
step S1, obtaining the destination position of the current user;
step S2, determining interest points to be recommended within a preset distance range from the destination position;
and step S3, recommending the current user based on the interest points to be recommended.
14. A computer readable storage medium having computer readable code stored therein, which when executed by one or more processors, causes the processors to perform the steps of:
step S1, obtaining the destination position of the current user;
step S2, determining interest points to be recommended within a preset distance range from the destination position;
and step S3, recommending the current user based on the interest points to be recommended.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
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| CN113822594A (en) * | 2021-09-30 | 2021-12-21 | 阿里巴巴新加坡控股有限公司 | Interest point grading determination method, electronic equipment and computer program product |
| CN113868532A (en) * | 2021-09-30 | 2021-12-31 | 北京百度网讯科技有限公司 | Location recommendation method and device, electronic equipment and storage medium |
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| CN111782955A (en) * | 2020-07-01 | 2020-10-16 | 支付宝(杭州)信息技术有限公司 | Interest point representing and pushing method and device, electronic equipment and storage medium |
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| CN113822594A (en) * | 2021-09-30 | 2021-12-21 | 阿里巴巴新加坡控股有限公司 | Interest point grading determination method, electronic equipment and computer program product |
| CN113868532A (en) * | 2021-09-30 | 2021-12-31 | 北京百度网讯科技有限公司 | Location recommendation method and device, electronic equipment and storage medium |
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