A location recommendation method, device, equipment and storage medium

Abstract

The embodiments of the present invention disclose a location recommendation method, apparatus, device and storage medium, the method comprising: in response to a detected location recommendation request, obtaining a set of locations to be allocated corresponding to the location recommendation request; determining a target recommended location corresponding to the location recommendation request according to the weight of each location to be allocated in the set of locations to be allocated, wherein the weight represents the priority of the corresponding location to be allocated being recommended, and the weight is determined according to the historical selection state of the corresponding location to be allocated; and generating response information of the location recommendation request according to the target recommended location. The location recommendation method provided in the embodiments of the present invention adjusts the weight of the location through the user's selection of the location, and recommends the location to the user according to the weight of the location, so that the location recommendation method is suitable for viewing areas of different playback types and different layouts, thereby improving the location recommendation effect.

Description

Technical Field

[0001] Embodiments of the present invention relate to the field of computer technology, and in particular to a location recommendation method, device, equipment and storage medium. Background Art

[0002] With the rapid development of mobile Internet, more and more users choose to buy tickets for movies, plays, musicals, etc. online. When purchasing, the choice of seats is crucial to the viewing effect and experience. Existing ticketing systems generally have the function of "recommending seat selection" for users. At present, the ticketing system generally recommends seat selection for users in the following way: determine the best viewing position in the viewing area, and then start recommending from the best viewing position. The closer to the best viewing position, the better the viewing position is by default, and then radiate to the surrounding areas and gradually spread outward.

[0003] In the process of implementing the present invention, the inventors found that there are at least the following technical problems in the prior art: the location recommendation method in the prior art is relatively fixed, and the location recommendation effect is relatively poor. Summary of the invention

[0004] The embodiments of the present invention provide a location recommendation method, apparatus, device and storage medium to achieve flexible location recommendation for users and improve the location recommendation effect.

[0005] In a first aspect, an embodiment of the present invention provides a location recommendation method, including:

[0006] In response to the detected location recommendation request, obtaining a set of locations to be allocated corresponding to the location recommendation request;

[0007] Determine the target recommended location corresponding to the location recommendation request according to the weight of each location to be allocated in the set of locations to be allocated, wherein the weight represents the priority of the corresponding location to be allocated being recommended, and the weight is determined according to the historical selection state of the corresponding location to be allocated;

[0008] Generate response information of the location recommendation request according to the target recommended location and respond.

[0009] In a second aspect, an embodiment of the present invention further provides a location recommendation device, including:

[0010] A to-be-allocated location acquisition module, configured to, in response to a detected location recommendation request, acquire a to-be-allocated location set corresponding to the location recommendation request;

[0011] A target location determination module, used to determine a target recommended location corresponding to the location recommendation request according to the weight of each location to be allocated in the set of locations to be allocated, wherein the weight represents the priority of the corresponding location to be allocated being recommended, and the weight is determined according to the historical selection state of the corresponding location to be allocated;

[0012] The response information generation module is used to generate response information of the location recommendation request according to the target recommended location.

[0013] In a third aspect, an embodiment of the present invention further provides a computer device, the device comprising:

[0014] one or more processors;

[0015] A storage device for storing one or more programs;

[0016] When one or more programs are executed by one or more processors, the one or more processors implement the location recommendation method provided by any embodiment of the present invention.

[0017] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a location recommendation method as provided in any embodiment of the present invention.

[0018] The embodiment of the present invention obtains a set of to-be-allocated positions corresponding to the position recommendation request in response to the detected position recommendation request; determines the target recommended position corresponding to the position recommendation request according to the weight of each to-be-allocated position in the to-be-allocated position set, wherein the weight represents the priority of the corresponding to-be-allocated position being recommended, and the weight is determined according to the historical selection state of the corresponding to-be-allocated position; and generates response information of the position recommendation request according to the target recommended position. The weight of the position is adjusted according to the user's selection of the position, and the position is recommended to the user according to the weight of the position, so that the position recommendation method is suitable for viewing areas of different playback types and layouts, thereby improving the position recommendation effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 is a flow chart of a location recommendation method provided by Embodiment 1 of the present invention;

[0020] Figure 2 is a flow chart of a location recommendation method provided by Embodiment 2 of the present invention;

[0021] Figure 3 is a flow chart of a location recommendation method provided by Embodiment 3 of the present invention;

[0022] Figure 4 is a structural diagram of a location recommendation device provided by a fourth embodiment of the present invention;

[0023] Figure 5 It is a structural diagram of a computer device provided in Embodiment 5 of the present invention. DETAILED DESCRIPTION

[0024] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only parts related to the present invention, rather than all structures, are shown in the accompanying drawings.

[0025] Embodiment 1

[0026] Figure 1 1 is a flow chart of a location recommendation method provided by an embodiment of the present invention. This embodiment is applicable to the case of recommending a location to a user, and is particularly applicable to the case of recommending a movie location to a user. The method can be executed by a location recommendation device, which can be implemented in software and / or hardware. For example, the location recommendation device can be configured in a computer device. Figure 1 As shown, the method includes:

[0027] S110 . In response to the detected location recommendation request, obtain a set of locations to be allocated corresponding to the location recommendation request.

[0028] In this embodiment, the location recommendation request may be a request for obtaining a recommended location triggered by a user through an operation terminal. Optionally, the user may input relevant information of a location to be recommended (such as a location recommendation area, a location recommendation quantity, etc.) on a display interface of the operation terminal to trigger a location recommendation request. After the operation terminal generates a location recommendation request based on the information input by the user, the location recommendation request is sent to the location recommendation device. The location recommendation device parses the received location recommendation request and obtains a set of locations to be allocated corresponding to the location recommendation request.

[0029] The application scenario of the location recommendation method provided by the embodiment of the present invention is not limited here. For example, the location recommendation method can be applied to the recommendation of viewing locations, and can also be applied to the recommendation of viewing locations for dramas, concerts, and musicals. Taking the recommendation of viewing locations as an example, the user can input the relevant information of the viewing location to be recommended (such as viewing times, number of viewing locations, etc.) on the display interface of the operation terminal to trigger a location recommendation request. After the operation terminal generates a location recommendation request based on the information input by the user, it sends the location recommendation request to the location recommendation device. The location recommendation device parses the received location recommendation request, obtains the target theater corresponding to the viewing times, and uses the set of free locations in the target theater as the set of locations to be allocated.

[0030] S120: Determine a target recommended position corresponding to the position recommendation request according to the weight of each position to be allocated in the set of positions to be allocated.

[0031] The existing position recommendation methods have the technical problems of fixed recommendation methods and poor recommendation effects. Taking the recommendation of viewing position as an example, the existing viewing position recommendation methods rigidly treat all theaters or a certain type of theaters as homogeneous. However, even for the same movie, the best viewing positions in different theaters are different due to various factors. For example, the position of the theater's sound system, the sound system effect, the position of the door, the height difference between the front and back rows, the position of the air conditioner, the distance between the screen and the seat, etc. The above factors are all unique attributes of each theater, and the viewing position recommendation methods in the existing technology cannot be applied to different theaters at the same time.

[0032] In order to solve the above problems, this embodiment provides a method for recommending viewing positions that is universal for each viewing area (such as a theater, a playback hall, etc.), which can recommend the best viewing seats that are fully considered according to the specific attributes of different areas. Optionally, in this embodiment, for each position, a position recommendation is made to the user according to the weight of each position to be recommended, wherein the weight represents the priority of the corresponding position to be assigned, and the larger the weight value, the higher the priority of the position to be assigned corresponding to the weight, and the weight is determined according to the historical selection status of the corresponding position to be assigned. In other words, this embodiment adjusts the weight of the position related to the position selection operation according to the user's selection status of the position when the user selects the position, and recommends the position to the subsequent user according to the weight of each position. Exemplarily, after obtaining the weight of each position to be assigned, the weight of each position to be assigned is used as the selection basis, and the target recommended position is selected from each position to be assigned according to the user's position recommendation needs.

[0033] The location recommendation method provided in this embodiment can mine various influencing factors in the area corresponding to the location recommendation request according to the location selection operation of each user, and provide users with better recommended locations. Taking the recommendation of movie viewing locations as an example, according to the weight of each location to be assigned, the target recommended location provided to the user can be determined to exclude some locations with good locations but poor viewing effects due to factors such as the speakers being too close or the air conditioner blowing directly. And the recommendation results generated by the location recommendation method provided in this embodiment are not static, but will be dynamically adjusted according to the increase in the number of moviegoers and their experience, providing users with the best viewing experience in real time.

[0034] In one embodiment of the present invention, determining the target recommended location corresponding to the location recommendation request according to the weight of each to-be-allocated location in the to-be-allocated location set includes: obtaining the number of location recommendations corresponding to the location recommendation request; sorting the to-be-allocated locations in reverse order according to the weights of the to-be-allocated locations, and obtaining the to-be-allocated locations of the recommended number of locations in sequence according to the sorting order as the target recommended locations. Optionally, the user's location recommendation requirement may be the number of locations required by the user, that is, the number of location recommendations. The number of location recommendations may be obtained directly from the location recommendation request. After obtaining the number of location recommendations, the number of to-be-allocated locations of the recommended number of locations are obtained according to the weight sorting as the target recommended locations. Exemplarily, assuming that the number of recommended positions is 2, the combination of positions to be allocated includes position 1 to be allocated, position 2 to be allocated and position 3 to be allocated, the weight of position 1 to be allocated is 61, the weight of position 2 to be allocated is 60, and the weight of position 3 to be allocated is 59. After sorting the positions to be allocated in reverse order according to the weights, the sorting results are: position 1 to be allocated, position 2 to be allocated, and position 3 to be allocated. According to the sorting order, 2 positions to be allocated (position 1 to be allocated and position 2 to be allocated) are obtained in sequence as the target recommended positions.

[0035] In the above process of determining the target recommended position, there may be a situation where the weights corresponding to different positions to be allocated are the same. If there are different recommended positions to be allocated with the same weight, the positions to be allocated with the same weight can be sorted according to the distance between each position to be allocated and the initial point. The closer the distance to the initial point, the higher the ranking of the corresponding position to be allocated. For example, assuming that the set of positions to be allocated includes position 1 to be allocated, position 2 to be allocated, position 3 to be allocated and position 4 to be allocated, the weight of position 1 to be allocated is 61, the weight of position 2 to be allocated is 60, the weight of position 3 to be allocated is 59, the weight of position 4 to be allocated is 60, and the distance between position 2 to be allocated and the initial point is 1, and the distance between position 4 to be allocated and the initial point is 2, then the sorting results obtained after sorting the positions to be allocated are: position 1 to be allocated, position 2 to be allocated, position 4 to be allocated, and position 3 to be allocated. If there are different positions to be allocated with the same weight and the same distance from the initial point, the positions to be allocated can also be sorted in combination with other factors related to user needs. For example, assuming that the number of recommended positions is 2, the sorting order of different positions to be allocated with the same weight and the same distance from the initial point can also be determined in combination with the distance from the position to be allocated with the highest weight. The initial point is pre-set and is the best position when only the position factor is considered. Taking the viewing position as an example, the initial point may be the center of the theater, the intersection of the longitudinal front third and the horizontal central axis, the intersection of the longitudinal rear third and the horizontal central axis, etc.

[0036] S130: Generate response information of the location recommendation request according to the target recommended location.

[0037] After determining the target recommended location, add a recommendation mark to the target recommended location, generate a response page for the location recommendation request, and respond with it as the response information of the location recommendation request. Exemplarily, a line mark with a striking color can be added around the target recommended location. Optionally, a location selection control can also be automatically displayed at the target recommended location to replace the user's operation of selecting the target recommended location.

[0038] The embodiment of the present invention obtains a set of to-be-allocated positions corresponding to the position recommendation request in response to the detected position recommendation request; determines the target recommended position corresponding to the position recommendation request according to the weight of each to-be-allocated position in the to-be-allocated position set, wherein the weight represents the priority of the corresponding to-be-allocated position being recommended, and the weight is determined according to the historical selection state of the corresponding to-be-allocated position; and generates response information of the position recommendation request according to the target recommended position. The weight of the position is adjusted according to the user's selection of the position, and the position is recommended to the user according to the weight of the position, so that the position recommendation method is suitable for areas with different playback types and different layouts, thereby improving the position recommendation effect.

[0039] Embodiment 2

[0040] Figure 2 1 is a flow chart of a location recommendation method provided by the second embodiment of the present invention. This embodiment adds an operation of adjusting the location weight according to the user's selection based on the above embodiment. Figure 2 As shown, the method includes:

[0041] S210 . In response to the detected location recommendation request, obtain a set of locations to be allocated corresponding to the location recommendation request.

[0042] S220: Determine a target recommended position corresponding to the position recommendation request according to the weight of each position to be allocated in the set of positions to be allocated.

[0043] S230: Generate response information of the location recommendation request according to the target recommended location.

[0044] S240: Obtain a target selection position corresponding to the response information, and adjust a weight of a target recommendation position according to the target selection position.

[0045] In this embodiment, after the target recommended position is displayed to the user through the response information, the target selection position finally confirmed by the user is obtained, and the weight of the target recommended position is adjusted according to the target selection position selected by the user. Optionally, before the weight of the target recommended position is adjusted, the weight of the target recommended position can be the weight of the target recommended position generated by the historical user's position selection operation, and can also be the initial weight of the target recommended position. Among them, the initial weight of the target recommended position can be a set value, and can also be determined based on the user's scoring, voting and other operations on the target recommended position, and can also be determined based on the purchase situation of the historical target recommended position and the position-related score situation.

[0046] In one embodiment of the present invention, adjusting the weight of the target recommended position according to the target selected position includes: obtaining the selected position identifier of the target selected position and the recommended position identifier of the target recommended position, matching the selected position identifier with the recommended position identifier; if the selected position identifier matches the recommended position identifier successfully, the weight of the target recommended position is adjusted upward; if the selected position identifier matches the recommended position identifier unsuccessfully, the weight of the target recommended position is adjusted downward. Specifically, adjusting the weight of the target recommended position according to the target selected position can be specifically: if the target selected position is the target recommended position, that is, the user selects the target recommended position, the weight of the target recommended position is adjusted upward; if the target selected position is not the target recommended position, that is, the user does not select the target recommended position, the weight of the target recommended position is adjusted downward. According to the user's selection operation of the target recommended position, factors other than the position factor that may affect the viewing effect of the target recommended position can be mined. Adjusting the weight of the target recommended position is equivalent to adjusting the recommendation priority of the position according to the mined factors, so that the position recommendation can be dynamically adjusted with the increase in the number of viewers and experience, and the best viewing experience is provided to the user in real time.

[0047] In one embodiment, the weight of the target recommended position is increased, including: determining the weight increase value of the target recommended position according to a preset increase coefficient and the user weight corresponding to the position recommendation request; and increasing the weight of the target recommended position according to the weight increase value of the target recommended position. Optionally, an increase coefficient may be preset, and the weight increase value may be determined according to the user weight corresponding to the position recommendation request and the increase coefficient, and the weight increase value may be added to the weight of the target recommended position to obtain the weight of the target recommended position after the weight increase. Exemplarily, the weight increase value may be determined according to the preset increase coefficient and the user weight corresponding to the position recommendation request. h =a*W determines the weight increase value, s h is the weight increase value, a is the increase coefficient, and W is the user weight corresponding to the location recommendation request. The user weight can be determined based on the number of times the user has viewed the location area. For example, the user weight can be calculated by W=N s / N t OK, Ns is the number of views by users in the location area, N t is the total number of views by all users in the location area. Taking watching movies as an example, N s is the number of times the user has watched in the theater, N t The total number of views by all users of this theater.

[0048] In one embodiment, the weight of the target recommended position is lowered, including: determining the weight lowering value of the target recommended position according to a preset lowering coefficient and the user weight corresponding to the position recommendation request; and lowering the weight of the target recommended position according to the weight lowering value of the target recommended position. The weight lowering method is similar to the weight raising method. Optionally, a lowering coefficient may be preset, and the weight lowering value may be determined according to the user weight corresponding to the position recommendation request and the lowering coefficient. The weight of the target recommended position after the weight lowering value is subtracted from the weight of the target recommended position. Exemplarily, the weight lowering value may be calculated based on the s l = b*W determines the weight increase value, s l is the weight down-adjustment value, b is the down-adjustment coefficient, and W is the user weight corresponding to the location recommendation request. The user weight can be determined based on the number of times the user has viewed the location area. For example, the user weight can be calculated by W=N s / N t OK, N s is the number of views by users in the location area, N t is the total number of views by all users in the location area. Taking watching movies as an example, N s is the number of times the user watched in the theater, N t The total number of views by all users of this theater.

[0049] It should be noted that, in this embodiment, the upward adjustment coefficient and the downward adjustment coefficient can be set according to actual needs, but in order to make the weight adjustment more reasonable, the upward adjustment coefficient needs to be smaller than the downward adjustment coefficient. In addition, in order to make the adjustment of the position weight more reasonable, the upper limit of the total score of each user's influence on a single position can be set to ensure that no individual user will affect the weight of a single position to a large extent. Using the user weight as a parameter for adjusting the position weight value can achieve the recommendation of positions for subsequent users based on the user's actual viewing experience. The user determines the viewing effect priority of a specific position. The more users watch, the greater the influence and the more accurate the result.

[0050] In one embodiment of the present invention, it also includes: if the selection position identifier fails to match the recommended position identifier, the weight of the target selection position is adjusted upward. Optionally, when the target selection position is not the target recommended position, on the basis of lowering the weight of the target recommended position, the weight of the target selection position can also be adjusted upward, so that the recommendation priority of the target recommended position is reduced while the recommendation priority of the target selection position is increased. Optionally, a more detailed method of increasing the weight of the target selection position can be found in the above embodiment, which will not be repeated here.

[0051] Based on the above embodiments, the embodiments of the present invention add an operation of adjusting the weight of the target recommendation position according to the target selection position selected by the user. According to the user's selection operation of the target recommendation position, factors that may affect the viewing effect of the target recommendation position in addition to the position factor can be discovered, so that the position recommendation can be dynamically adjusted with the increase in the number of viewers and their experience, thereby providing users with the best viewing experience in real time.

[0052] Embodiment 3

[0053] Figure 3 1 is a flow chart of a location recommendation method provided by Embodiment 3 of the present invention. Based on the above embodiments, this embodiment takes the recommendation of movie viewing location as an example to provide a preferred embodiment. Figure 3 As shown, the method includes:

[0054] S301. Start.

[0055] S302: According to the seat weight values, recommend the seat with the highest weight value to the user.

[0056] In this embodiment, the seat weight value may be an initial weight value, or a seat weight value generated by a historical user selection operation. Optionally, taking the number of recommended positions as 1 as an example, the seat with the highest seat weight value may be selected as the recommended seat according to the seat weight value table. If multiple seats are tied for the first score, the one closer to the initial point is given priority.

[0057] The initial weight value is the weight value of the seat after initialization. Optionally, the intersection of the longitudinal third of the theater and the horizontal central axis (if it is between two seats, the right side shall prevail) can be used as the initial point, and the weight of the initial point is set to 60. Starting from the initial point, the scores are reduced by 0.5 in the surrounding areas until the scores of the entire seat map are calculated, and the initial weight values ​​of each seat in the theater are obtained.

[0058] S303: Calculate the user's influence on the theater.

[0059] Optionally, the user influence may be the ratio of the number of times the user watches movies in the theater to the total number of times all users in the theater watch movies. The more times the user watches movies in the theater, the greater the score influence.

[0060] S304: Determine whether the user influence score exceeds a set score.

[0061] The upper limit of the total score of each user's influence on a single seat can be set to no more than 0.5 points, and it is determined whether the influence score of the user on the recommended seat exceeds 0.5. If the influence score of the user on the recommended seat exceeds 0.5, S311 is executed to end the adjustment operation of the seat influence score. If the influence score of the user on the recommended seat does not exceed 0.5, S305 is executed to continue adjusting the seat weight value according to the user's selection operation.

[0062] S305: Whether the user accepts.

[0063] Determine whether the user accepts the seat recommendation, that is, determine whether the user's selected seat is consistent with the recommended seat. If the user's selected seat is consistent with the recommended seat, it means that the user accepts the seat recommendation, and execute S306; if the user's selected seat is inconsistent with the recommended seat, it means that the user does not accept the seat recommendation, and execute S307.

[0064] S306: Determine the floating weight value of the seat.

[0065] If the user accepts this recommendation, the weight value of the seat will increase. The increased weight value can be calculated by increased weight value = 0.1*user influence, where 0.1 is the increase coefficient.

[0066] S307: Determine the seat drop weight value.

[0067] If the user does not accept this recommendation and manually selects another seat, the score of the seat will decrease. The decreased weight value can be calculated by decreased weight value = 0.15*user influence, where 0.15 is the downward floating coefficient.

[0068] S308: Whether the user manually selects a seat.

[0069] Determine whether the user manually selects the seat. If the user manually selects the seat, increase the seat weight value of the seat manually selected by the user.

[0070] S309: Determine the floating weight value of the manually selected seat.

[0071] The method for determining the floating weight value of the manually selected seat can refer to S306.

[0072] S310. Update the seat weight value table.

[0073] The seat weight value table in the theater is updated according to the upward weight value and downward weight value of the seat, which will be used as the standard for the next seat selection.

[0074] S311, end.

[0075] The technical solution of the embodiment of the present invention can accurately determine whether a specific seat in the theater has the best viewing experience through the viewing experience of users at various positions. It can effectively solve the problem of different viewing experiences at different positions for different types of films (2D, 3D, IMAX, etc.). It can be accurate to the differences in specific theaters and specific seats. It can even determine unfavorable factors such as the location of the door and whether the air conditioner is blowing directly, and truly recommend the best viewing seat among the remaining seats in the theater.

[0076] Embodiment 4

[0077] Figure 4 is a schematic diagram of the structure of a location recommendation device provided by Embodiment 4 of the present invention. The location recommendation device may be implemented in software and / or hardware, for example, the location recommendation device may be configured in a computer device. Figure 4 As shown, the device includes a to-be-allocated position acquisition module 410, a target position determination module 420 and a response information generation module 430, wherein:

[0078] The to-be-allocated location acquisition module 410 is configured to, in response to the detected location recommendation request, acquire a to-be-allocated location set corresponding to the location recommendation request;

[0079] The target location determination module 420 is used to determine the target recommended location corresponding to the location recommendation request according to the weight of each location to be allocated in the set of locations to be allocated, wherein the weight represents the priority of the corresponding location to be allocated being recommended, and the weight is determined according to the historical selection state of the corresponding location to be allocated;

[0080] The response information generating module 430 is used to generate response information of the location recommendation request according to the target recommended location to respond.

[0081] In the embodiment of the present invention, the to-be-allocated position acquisition module responds to the detected position recommendation request and acquires the to-be-allocated position set corresponding to the position recommendation request; the target position determination module determines the target recommended position corresponding to the position recommendation request according to the weight of each to-be-allocated position in the to-be-allocated position set, wherein the weight represents the priority of the corresponding to-be-allocated position being recommended, and the weight is determined according to the historical selection status of the corresponding to-be-allocated position; the response information generation module generates response information of the position recommendation request according to the target recommended position. The weight of the position is adjusted by the user's selection of the position, and the position is recommended to the user according to the weight of the position, so that the position recommendation method is suitable for areas with different playback types and different layouts, thereby improving the position recommendation effect.

[0082] Optionally, based on the above solution, the target location determination module 420 is specifically used to:

[0083] Get the number of location recommendations corresponding to the location recommendation request;

[0084] The positions to be allocated are sorted in reverse order according to their weights, and the positions to be allocated with a recommended number of positions are obtained in sequence according to the sorting order as target recommended positions.

[0085] Optionally, based on the above solution, the device further includes a weight adjustment module, which is used to:

[0086] After generating response information of the position recommendation request according to the target recommended position, the target selected position corresponding to the response information is obtained, and the weight of the target recommended position is adjusted according to the target selected position.

[0087] Optionally, based on the above solution, the weight adjustment module is specifically used for:

[0088] Obtaining a selected location identifier of a target selected location and a recommended location identifier of a target recommended location, and matching the selected location identifier with the recommended location identifier;

[0089] If the selected location identifier matches the recommended location identifier successfully, the weight of the target recommended location is increased;

[0090] If the selected location identifier fails to match the recommended location identifier, the weight of the target recommended location will be lowered.

[0091] Optionally, based on the above solution, the weight adjustment module is specifically used for:

[0092] Determine the weight increase value of the target recommended location according to the preset increase coefficient and the user weight corresponding to the location recommendation request;

[0093] The weight of the target recommended position is increased according to the weight increase value of the target recommended position.

[0094] Optionally, based on the above solution, the weight adjustment module is specifically used for:

[0095] Determine a weight reduction value of the target recommended location according to a preset reduction coefficient and a user weight corresponding to the location recommendation request;

[0096] The weight of the target recommended position is lowered according to the weight lowering value of the target recommended position.

[0097] Optionally, based on the above solution, the weight adjustment module is further used to:

[0098] If the selected location identifier fails to match the recommended location identifier, the weight of the target selected location is adjusted upward.

[0099] The location recommendation device provided in the embodiment of the present invention can execute the location recommendation method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0100] Embodiment 5

[0101] Figure 5 It is a structural diagram of a computer device provided in Embodiment 5 of the present invention. Figure 5 A block diagram of an exemplary computer device 512 suitable for use in implementing embodiments of the present invention is shown. Figure 5 The computer device 512 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0102] like Figure 5 As shown, the computer device 512 is in the form of a general-purpose computing device. The components of the computer device 512 may include, but are not limited to: one or more processors 516, a system memory 528, and a bus 518 that connects various system components (including the system memory 528 and the processor 516).

[0103] Bus 518 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a local bus to processor 516, or a bus structure using any of a variety of bus architectures. These architectures include, by way of example, but are not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MAC) bus, an Enhanced ISA bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus.

[0104] The computer device 512 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the computer device 512, including volatile and non-volatile media, removable and non-removable media.

[0105] System memory 528 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 530 and / or cache memory 532. Computer device 512 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, storage device 534 may be used to read and write non-removable, non-volatile magnetic media ( Figure 5 not shown, usually called a "hard drive"). Although Figure 5Not shown, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 518 via one or more data medium interfaces. The memory 528 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present invention.

[0106] A program / utility 540 having a set (at least one) of program modules 542 may be stored, for example, in the memory 528, such program modules 542 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. The program modules 542 generally perform the functions and / or methods of the embodiments described herein.

[0107] The computer device 512 may also communicate with one or more external devices 514 (e.g., keyboard, pointing device, display 524, etc.), may also communicate with one or more devices that enable a user to interact with the computer device 512, and / or communicate with any device that enables the computer device 512 to communicate with one or more other computing devices (e.g., network card, modem, etc.). Such communication may be performed via an input / output (I / O) interface 522. In addition, the computer device 512 may also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN) and / or public network, such as the Internet) via a network adapter 520. As shown, the network adapter 520 communicates with other modules of the computer device 512 via a bus 518. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the computer device 512, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0108] The processor 516 executes various functional applications and data processing by running the program stored in the system memory 528, such as implementing the location recommendation method provided in the embodiment of the present invention, which includes:

[0109] In response to the detected location recommendation request, obtaining a set of locations to be allocated corresponding to the location recommendation request;

[0110] Determine the target recommended location corresponding to the location recommendation request according to the weight of each location to be allocated in the set of locations to be allocated, wherein the weight represents the priority of the corresponding location to be allocated being recommended, and the weight is determined according to the historical selection state of the corresponding location to be allocated;

[0111] Generate response information of the location recommendation request according to the target recommended location.

[0112] Of course, those skilled in the art can understand that the processor can also implement the technical solution of the location recommendation method provided by any embodiment of the present invention.

[0113] Embodiment 6

[0114] Embodiment 6 of the present invention further provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the location recommendation method provided in the embodiment of the present invention is implemented. The method includes:

[0115] In response to the detected location recommendation request, obtaining a set of locations to be allocated corresponding to the location recommendation request;

[0116] Determine the target recommended location corresponding to the location recommendation request according to the weight of each location to be allocated in the set of locations to be allocated, wherein the weight represents the priority of the corresponding location to be allocated being recommended, and the weight is determined according to the historical selection state of the corresponding location to be allocated;

[0117] Generate response information of the location recommendation request according to the target recommended location.

[0118] Of course, the computer program stored in a computer-readable storage medium provided by an embodiment of the present invention is not limited to the operations of the method described above, but can also execute related operations of the location recommendation method provided by any embodiment of the present invention.

[0119] The computer storage medium of the embodiment of the present invention can adopt any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, 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 portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer-readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it.

[0120] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0121] Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0122] Computer program code for performing the operations of the present invention may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0123] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A location recommendation method, characterized in that: include: In response to the detected location recommendation request, obtaining a set of locations to be allocated corresponding to the location recommendation request; Determining a target recommended location corresponding to the location recommendation request according to a weight of each location to be allocated in the set of locations to be allocated, wherein the weight represents a priority of the corresponding location to be allocated being recommended, and the weight is determined according to a historical selection state of the corresponding location to be allocated; Generate response information of the location recommendation request according to the target recommended location to respond; The step of determining the target recommended location corresponding to the location recommendation request according to the weight of each location to be allocated in the set of locations to be allocated includes: Obtaining the number of location recommendations corresponding to the location recommendation request; Sorting the positions to be allocated in reverse order according to the weights of the positions to be allocated, and sequentially acquiring the recommended number of positions to be allocated as the target recommended positions according to the sorting order; The step of sorting the positions to be allocated in reverse order according to the weights of the positions to be allocated includes: if there are different recommended positions to be allocated with the same weight, sorting the positions to be allocated with the same weight according to the distance between each position to be allocated and the initial point, the closer the distance to the initial point, the higher the ranking of the corresponding position to be allocated, wherein the initial point is pre-set and is the best position when only the position factor is considered; After generating the response information of the location recommendation request according to the target recommended location to respond, the method further includes: Acquire a target selection position corresponding to the response information, and adjust a weight of the target recommendation position according to the target selection position; The step of adjusting the weight of the target recommendation position according to the target selection position includes: Acquire a selection position identifier of the target selection position and a recommended position identifier of the target recommended position, and match the selection position identifier with the recommended position identifier; If the selected location identifier matches the recommended location identifier successfully, determining a weight increase value of the target recommended location according to a preset increase coefficient and a user weight corresponding to the location recommendation request; and increasing the weight of the target recommended location according to the weight increase value of the target recommended location; If the selected location identifier fails to match the recommended location identifier, determining a weight reduction value of the target recommended location according to a preset reduction coefficient and a user weight corresponding to the location recommendation request; and reducing the weight of the target recommended location according to the weight reduction value of the target recommended location; The user weight is the ratio of the number of views of the user in the location area to the total number of views of all users in the location area.

2. The method according to claim 1, characterized in that Also includes: If the selected location identifier fails to match the recommended location identifier, the weight of the target selected location is increased.

3. A location recommendation device, characterized in that: include: A to-be-allocated location acquisition module, configured to, in response to a detected location recommendation request, acquire a to-be-allocated location set corresponding to the location recommendation request; a target location determination module, configured to determine a target recommended location corresponding to the location recommendation request according to a weight of each location to be allocated in the set of locations to be allocated, wherein the weight represents a priority of the corresponding location to be allocated being recommended, and the weight is determined according to a historical selection state of the corresponding location to be allocated; A response information generating module, used for generating response information of the location recommendation request according to the target recommended location to respond; Wherein, the target location determination module is specifically used for: Obtaining the number of location recommendations corresponding to the location recommendation request; Sorting the positions to be allocated in reverse order according to the weights of the positions to be allocated, and sequentially acquiring the recommended number of positions to be allocated as the target recommended positions according to the sorting order; The step of sorting the positions to be allocated in reverse order according to the weights of the positions to be allocated includes: if there are different recommended positions to be allocated with the same weight, sorting the positions to be allocated with the same weight according to the distance between each position to be allocated and the initial point, the closer the distance to the initial point, the higher the ranking of the corresponding position to be allocated, wherein the initial point is pre-set and is the best position when only the position factor is considered; The device also includes a weight adjustment module, which is used to: After generating a response message of the location recommendation request according to the target recommended location, obtaining a target selection location corresponding to the response message, and adjusting a weight of the target recommended location according to the target selection location; The weight adjustment module is specifically used for: Acquire a selection position identifier of the target selection position and a recommended position identifier of the target recommended position, and match the selection position identifier with the recommended position identifier; If the selected location identifier matches the recommended location identifier successfully, determining a weight increase value of the target recommended location according to a preset increase coefficient and a user weight corresponding to the location recommendation request; and increasing the weight of the target recommended location according to the weight increase value of the target recommended location; If the selected location identifier fails to match the recommended location identifier, determining a weight reduction value of the target recommended location according to a preset reduction coefficient and a user weight corresponding to the location recommendation request; and reducing the weight of the target recommended location according to the weight reduction value of the target recommended location; The user weight is the ratio of the number of views of the user in the location area to the total number of views of all users in the location area.

4. A computer device, characterized in that: The device comprises: one or more processors; A storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the location recommendation method as described in any one of claims 1-2.

5. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the location recommendation method as described in any one of claims 1-2 is implemented.

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