Group purchase product recommendation method, device, equipment and storage medium

Abstract

The present invention belongs to the field of computer technology and discloses a method, apparatus, device, and storage medium for recommending group-purchased goods. The method includes: upon receiving an access request from a target terminal, obtaining the current location, user information, purchase history, and browsing history corresponding to the target terminal; determining the community corresponding to the target terminal based on the current location; constructing a user profile corresponding to the target terminal based on the user information, purchase history, and browsing history; determining several product types corresponding to the user profile; and recommending suitable group-purchased goods to the target terminal based on the community and several product types. Through the above-mentioned method, the user profile corresponding to the target terminal is determined, and group-purchased goods are recommended based on the product types corresponding to the user profile and the community where the target terminal is located. This realizes automatic acquisition of user needs, recommends group-purchased goods based on user needs, and improves the user shopping experience.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a method, apparatus, device and storage medium for recommending group-buying products. Background Art

[0002] Currently, users search for desired products by browsing websites or typing keywords into the website's search engine to confirm whether a group buy of the desired products is in progress. Existing group buying platforms are unable to timely understand user needs and dynamically recommend group buy products based on user needs, so group buying often fails to achieve the expected results.

[0003] The above content is only used to assist in understanding the technical solution of the present invention and does not constitute an admission that the above content is prior art. Summary of the Invention

[0004] The main purpose of the present invention is to provide a group purchase commodity recommendation method, device, equipment and storage medium, aiming to solve the technical problem that existing group purchase platforms are unable to obtain user needs in a timely manner and dynamically recommend group purchase commodities based on user needs.

[0005] To achieve the above object, the present invention provides a method for recommending group-buying products, the method comprising the following steps:

[0006] Upon receiving an access request from a target terminal, obtaining the current location, user information, purchase history, and browsing history corresponding to the target terminal;

[0007] Determining a community corresponding to the target terminal according to the current location;

[0008] Constructing a user profile corresponding to the target terminal based on the user information, the purchase history, and the browsing history;

[0009] Determine several product types corresponding to the user profile;

[0010] Recommend suitable group-buying products to the target terminal based on the community and the multiple product types.

[0011] Optionally, before determining the community corresponding to the target terminal according to the current location, the method further includes:

[0012] Determine the location information corresponding to each group purchasing user in the group purchasing record of each product;

[0013] Reading an initial community division grid, and determining an initial community corresponding to the location information according to the initial community division grid;

[0014] Clustering is performed based on the group purchase records and the corresponding multiple initial communities to obtain a target community division grid;

[0015] The determining, according to the current location, a community corresponding to the target terminal includes:

[0016] Determine the community grid where the current location is located according to the target community grid division;

[0017] The community corresponding to the target terminal is determined based on the community grid.

[0018] Optionally, constructing a user profile corresponding to the target terminal based on the user information, the purchase record, and the browsing record includes:

[0019] Obtaining portrait features from the user information, the purchase history, and the browsing history;

[0020] A user portrait corresponding to the target terminal is constructed based on the portrait features.

[0021] Optionally, the recommending suitable group-buying products to the target terminal based on the community and the multiple product types includes:

[0022] Filtering all group-purchased products based on the community and the multiple product types to obtain multiple group-purchased products;

[0023] Sorting the group-purchased products to obtain a recommended order of products;

[0024] Recommend suitable group-buying products to the target terminal according to the product recommendation order.

[0025] Optionally, the sorting of the group-purchased products to obtain a recommended order of products includes:

[0026] Obtaining graphic and text description information, purchase volume, and favorable review rate corresponding to the group-purchased products;

[0027] Determine a product rating corresponding to each of the group-purchased products based on the graphic description information, the purchase volume, and the favorable review rate;

[0028] The group-purchased products are sorted based on the product ratings to obtain a product recommendation order.

[0029] Optionally, after constructing the user profile corresponding to the target terminal based on the user information, the purchase history, and the browsing history, the method further includes:

[0030] The corresponding published life circle content is pushed to the target terminal based on the community and the user portrait.

[0031] Optionally, the pushing corresponding published life circle content to the target terminal based on the community and the user portrait includes:

[0032] Determining a number of corresponding seller users based on the community;

[0033] Determine a number of buyer users corresponding to the user profile, wherein the similarity between the target user profile corresponding to the buyer user and the user profile is greater than a preset threshold;

[0034] The published life circle contents corresponding to the plurality of seller users and the plurality of buyer users are obtained and pushed to the target terminal.

[0035] In addition, to achieve the above-mentioned purpose, the present invention further provides a group purchase product recommendation device, which includes:

[0036] An acquisition module, configured to acquire the current location, user information, purchase history, and browsing history of a target terminal upon receiving an access request from the target terminal;

[0037] A determination module, configured to determine a community corresponding to the target terminal according to the current location;

[0038] A construction module, configured to construct a user profile corresponding to the target terminal based on the user information, the purchase record, and the browsing record;

[0039] The determination module is further configured to determine a number of commodity types corresponding to the user portrait;

[0040] A recommendation module is used to recommend suitable group-buying commodities to the target terminal based on the community and the multiple commodity types.

[0041] In addition, to achieve the above-mentioned purpose, the present invention also proposes a group-buying product recommendation device, which includes: a memory, a processor, and a group-buying product recommendation program stored on the memory and executable on the processor, wherein the group-buying product recommendation program is configured to implement the group-buying product recommendation method described above.

[0042] In addition, to achieve the above-mentioned purpose, the present invention further proposes a storage medium, on which a group-buying product recommendation program is stored. When the group-buying product recommendation program is executed by a processor, the group-buying product recommendation method described above is implemented.

[0043] The present invention obtains the current location, user information, purchase history, and browsing history of the target terminal upon receiving an access request from the target terminal; determines the community corresponding to the target terminal based on the current location; constructs a user profile corresponding to the target terminal based on the user information, purchase history, and browsing history; determines several product types corresponding to the user profile; and recommends suitable group-buying products to the target terminal based on the community and several product types. Through the above-mentioned method, the user profile corresponding to the target terminal is determined, and group-buying products are recommended based on the product types corresponding to the user profile and the community where the target terminal is located. This achieves automatic acquisition of user needs and recommendation of group-buying products based on user needs, thereby improving the user shopping experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 It is a structural diagram of a group purchase commodity recommendation device in a hardware operating environment involved in an embodiment of the present invention;

[0045] Figure 2 This is a flow chart of a first embodiment of the group purchase product recommendation method of the present invention;

[0046] Figure 3 This is a flow chart of a second embodiment of the group purchase product recommendation method of the present invention;

[0047] Figure 4 This is a structural block diagram of the first embodiment of the group purchase product recommendation device of the present invention.

[0048] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0049] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0050] Reference Figure 1 , Figure 1 This is a schematic diagram of the structure of a group purchase product recommendation device in the hardware operating environment involved in an embodiment of the present invention.

[0051] like Figure 1As shown, the group purchase product recommendation device may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Among them, the communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the user interface 1003 may optionally include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a wireless fidelity (Wireless-Fidelity, Wi-Fi) interface). The memory 1005 may be a high-speed random access memory (Random Access Memory, RAM) or a stable non-volatile memory (Non-Volatile Memory, NVM), such as a disk storage. The memory 1005 may optionally be a storage device independent of the aforementioned processor 1001.

[0052] Those skilled in the art will understand that Figure 1 The structure shown in the figure does not constitute a limitation on the group purchase product recommendation device, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0053] like Figure 1 As shown, the memory 1005 as a storage medium may include an operating system, a network communication module, a user interface module, and a group purchase product recommendation program.

[0054] exist Figure 1 In the group-buying product recommendation device shown, the network interface 1004 is mainly used for data communication with the network server; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and the memory 1005 in the group-buying product recommendation device of the present invention can be set in the group-buying product recommendation device, and the group-buying product recommendation device calls the group-buying product recommendation program stored in the memory 1005 through the processor 1001, and executes the group-buying product recommendation method provided by the embodiment of the present invention.

[0055] The embodiment of the present invention provides a method for recommending group-buying products. Figure 2 , Figure 2 This is a flow chart of the first embodiment of the group purchase product recommendation method of the present invention.

[0056] In this embodiment, the group purchase product recommendation method includes the following steps:

[0057] Step S10: upon receiving an access request from a target terminal, obtaining the current location, user information, purchase history, and browsing history corresponding to the target terminal.

[0058] It is understandable that the execution subject of this embodiment is the group purchase product recommendation device, which can be a computer, server or other device with the same or similar functions, and this embodiment does not limit this.

[0059] It should be noted that, for this example, the execution entity is a server with a group-buying platform installed. The target terminal has a corresponding client installed. When the target terminal activates the client based on a user operation, it sends an access request to the server. Based on the received access request, the server requests the target terminal's corresponding location information, obtains the current location, and queries the database based on the terminal identifier carried in the access request to obtain the target terminal's corresponding user information, purchase history, and browsing history. In the specific implementation, user information includes gender and age, purchase history includes multiple purchase records within a period of time, and browsing history includes multiple browsing records within a period of time.

[0060] In a specific implementation, the client launched by the target terminal includes functions such as homepage, community preferences, community group buying, local life circle, community stores, and personal center. This embodiment focuses on the "community group buying" function. When the target terminal launches the client and the user clicks the "community group buying" button to enter the community group buying page, the server obtains the current location, user information, purchase history, and browsing history based on the access request, and recommends suitable group buying products to the user based on the obtained information.

[0061] Step S20: Determine the community corresponding to the target terminal according to the current location.

[0062] It should be understood that in this embodiment, a community network that has been divided in advance is provided, and the community corresponding to the current location is determined in the community network.

[0063] Furthermore, before step S20, the method further includes: determining location information corresponding to each group purchasing user in the group purchasing record of each product; reading an initial community division grid, and determining an initial community corresponding to the location information based on the initial community division grid; performing clustering based on the group purchasing record and the corresponding multiple initial communities to obtain a target community division grid;

[0064] The step S20 includes: determining the community grid where the current location is located according to the target community grid division; and determining the community corresponding to the target terminal based on the community grid.

[0065] It should be noted that, to meet user needs, some products may only be sold in certain communities, and users in communities where these products are not sold may also have a need to purchase them. In this embodiment, clustering is performed based on the initial communities of each user in the group purchase records, multiple initial communities with high correlation are determined, and multiple initial communities with correlations greater than a preset correlation threshold are grouped into the same target community, thereby obtaining an adjusted target community division grid. The community where the target terminal is located is determined based on the current location, including multiple initial communities with high correlations.

[0066] Step S30: Construct a user profile corresponding to the target terminal based on the user information, the purchase history, and the browsing history.

[0067] It should be understood that multiple product keywords are extracted from multiple purchase records within a period of time, and multiple product keywords are extracted from multiple browsing records within a period of time, and the extracted multiple product keywords are deduplicated. Optionally, feature vectors are extracted from user information (gender and age) and product keywords; model classification: the feature vector is input into a pre-trained model for classification to determine the corresponding user portrait. In a specific implementation, the classification result of the pre-trained model corresponds to multiple pre-set feature portraits, and the model outputs the similarity between the feature vector and each feature portrait, and one or more feature portraits with a similarity greater than a preset similarity threshold are selected as the user portrait corresponding to the target terminal.

[0068] Optionally, the step S30 includes: obtaining portrait features from the user information, the purchase records, and the browsing records; and constructing a user portrait corresponding to the target terminal based on the portrait features.

[0069] It should be noted that product keywords are extracted from purchase records and browsing records, the extracted multiple product keywords are deduplicated, and each product keyword is assigned a corresponding correction weight based on the number of occurrences of each product keyword. A word vector corresponding to the user information and product keywords is generated, and the vector average value is calculated based on the word vector and the correction weight, and the vector average value is used as the portrait data corresponding to the target terminal.

[0070] Step S40: Determine several commodity types corresponding to the user portrait.

[0071] It should be understood that, optionally, the server stores the correspondence between each feature profile and each product type, with the user setting up a corresponding table based on actual circumstances, for example, corresponding between "esports youth" and "electronic products." Optionally, the server obtains portrait data corresponding to the user profile, classifies the portrait data according to a preset classification model, determines the similarity between the portrait data and each product type, and selects one or more product types with a similarity greater than a certain threshold as the product type corresponding to the user profile.

[0072] Step S50: Recommending suitable group-buying products to the target terminal based on the community and the multiple product types.

[0073] It should be noted that group-buying products that match the community and several product types are selected from all group-buying products for recommendation.

[0074] Specifically, the step S50 includes: screening all group-purchased products based on the community and the product types to obtain a number of group-purchased products; sorting the group-purchased products to obtain a product recommendation order; and recommending suitable group-purchased products to the target terminal according to the product recommendation order.

[0075] It should be understood that in this embodiment, when a user browses the homepage via the target terminal, the server determines the number of items to be displayed based on the layout information of the target terminal and recommends a corresponding number of group-buying items in the order of the items displayed. When the user swipes the screen to turn the page, the server determines the updated number based on the swipe instruction and recommends a corresponding number of group-buying items in the order of the items based on the updated number. Optionally, the group-buying items may be sorted based on their corresponding group-buying progress, for example, the group-buying item with the most progress ("only one person missing") is ranked first.

[0076] Furthermore, the sorting of the group-purchased products to obtain a recommended order of products includes: obtaining graphic and text description information, purchase volume, and praise rate corresponding to the group-purchased products; determining a product score corresponding to each of the group-purchased products based on the graphic and text description information, the purchase volume, and the praise rate; and sorting the group-purchased products based on the product score to obtain a recommended order of products.

[0077] It should be noted that the purchase volume intervals and level scores corresponding to each purchase level, and the praise rate intervals and level scores corresponding to each praise level are divided in advance. Determine the purchase volume intervals and the praise rate intervals corresponding to the purchase volumes of several group-purchased products, thereby determining the purchase levels and praise levels corresponding to several group-purchased products, and determine the purchase level scores and praise level scores based on the purchase levels and praise levels. Based on the graphic and text description information uploaded by the merchant, the group-purchased products are evaluated from three levels: the completeness of the text description, the quality of the picture, and the degree of consistency between the text and the picture, and the corresponding graphic and text scores are obtained. Determine the product score corresponding to each group-purchased product based on the purchase level score, the praise level score, the graphic and text score, and the preset weight ratio, and sort them in descending order according to the product score to obtain the product recommendation order.

[0078] In one implementation, the server analyzes the purchase records of the target terminal to determine the purchase rating, positive rating, and image rating of the products purchased by the user, and then takes the average purchase rating, positive rating, and image rating corresponding to multiple purchase records. The average purchase rating is compared with the standard purchase rating to determine the purchase volume attention corresponding to the target terminal; the average positive rating is compared with the standard positive rating to determine the positive rating rate attention corresponding to the target terminal; the average image rating is compared with the standard image rating to determine the image description attention corresponding to the target terminal; the purchase volume attention, positive rating, and image description attention are normalized to determine the preset weight ratio corresponding to the target terminal. The preset weight ratio of the target terminal is updated at regular intervals to recommend group purchase products that meet user needs and shopping habits.

[0079] This embodiment obtains the current location, user information, purchase history, and browsing history of the target terminal upon receiving an access request from the target terminal; determines the community corresponding to the target terminal based on the current location; constructs a user profile corresponding to the target terminal based on the user information, purchase history, and browsing history; determines several product types corresponding to the user profile; and recommends suitable group-buying products to the target terminal based on the community and several product types. By determining the user profile corresponding to the target terminal and recommending group-buying products based on the product types corresponding to the user profile and the community where the target terminal is located, this method automatically obtains user needs and recommends group-buying products based on user needs, thereby improving the user shopping experience.

[0080] refer to Figure 3 , Figure 3 This is a flow chart of the second embodiment of the group purchase product recommendation method of the present invention.

[0081] Based on the first embodiment described above, the group purchase product recommendation method of this embodiment further includes, after step S30:

[0082] Step S04: Pushing corresponding published life circle content to the target terminal based on the community and the user portrait.

[0083] It should be understood that this embodiment targets the "local life circle" function corresponding to the client. When the client is started on the target terminal and the user clicks the "local life circle" button to enter the life circle page, the server obtains the current location, user information, purchase records and browsing records according to the access request, and pushes appropriate published life circle content to the user based on the obtained information.

[0084] Specifically, the step S04 includes: determining several corresponding seller users based on the community; determining several buyer users corresponding to the user portrait, wherein the similarity between the target user portrait corresponding to the buyer user and the user portrait is greater than a preset threshold; obtaining the published life circle content corresponding to the several seller users and the several buyer users, and pushing it to the target terminal.

[0085] It should be noted that, optionally, in this embodiment, the user profile is one of multiple pre-set feature profiles, and similarities between the multiple feature profiles are pre-set. The similarity between the user profile of the target terminal and the other feature profiles is determined, and one or more feature profiles (including the feature profile corresponding to the user profile) whose similarity exceeds a preset threshold are selected to thereby determine the corresponding buyer users. Optionally, in this embodiment, similarities are calculated based on the profile data corresponding to the user profile and the profile data corresponding to each buyer user, and buyer users whose similarity exceeds the preset threshold are selected.

[0086] It can be understood that in this embodiment, the life circle content published by sellers serving the corresponding community and buyers whose user portrait similarity is greater than a preset threshold is pushed to the target terminal, which improves the hit rate of product push information and makes it easier for users to obtain seller description information and buyer evaluation information of products of interest, thereby improving the user's group buying experience.

[0087] This embodiment obtains the target terminal's current location, user information, purchase history, and browsing history upon receiving an access request from the target terminal; determines the target terminal's corresponding community based on the current location; constructs a user profile for the target terminal based on the user information, purchase history, and browsing history; and pushes corresponding published content to the target terminal based on the community and user profile. In addition to providing product recommendations, this embodiment also recommends content published by sellers or buyers based on user needs, helping users understand the actual situation of the desired products and improving their group buying experience.

[0088] In addition, an embodiment of the present invention further provides a storage medium on which a group-buying product recommendation program is stored. When the group-buying product recommendation program is executed by a processor, the group-buying product recommendation method described above is implemented.

[0089] Since the storage medium adopts all the technical solutions of all the above embodiments, it has at least all the beneficial effects brought by the technical solutions of the above embodiments, which will not be described one by one here.

[0090] Reference Figure 4 , Figure 4 This is a structural block diagram of the first embodiment of the group purchase product recommendation device of the present invention.

[0091] like Figure 4 As shown, the group purchase product recommendation device proposed in the embodiment of the present invention includes:

[0092] The acquisition module 10 is configured to acquire the current location, user information, purchase history, and browsing history corresponding to the target terminal upon receiving an access request from the target terminal.

[0093] The determination module 20 is configured to determine the community corresponding to the target terminal according to the current location.

[0094] The construction module 30 is used to construct a user portrait corresponding to the target terminal based on the user information, the purchase record and the browsing record.

[0095] The determination module 20 is further configured to determine several commodity types corresponding to the user portrait.

[0096] The recommendation module 40 is configured to recommend suitable group-buying products to the target terminal based on the community and the multiple product types.

[0097] It should be understood that the above is only an example and does not constitute any limitation to the technical solution of the present invention. In specific applications, those skilled in the art can make settings as needed, and the present invention does not impose any limitation on this.

[0098] This embodiment obtains the current location, user information, purchase history, and browsing history of the target terminal upon receiving an access request from the target terminal; determines the community corresponding to the target terminal based on the current location; constructs a user profile corresponding to the target terminal based on the user information, purchase history, and browsing history; determines several product types corresponding to the user profile; and recommends suitable group-buying products to the target terminal based on the community and several product types. By determining the user profile corresponding to the target terminal and recommending group-buying products based on the product types corresponding to the user profile and the community where the target terminal is located, this method automatically obtains user needs and recommends group-buying products based on user needs, thereby improving the user shopping experience.

[0099] It should be noted that the workflow described above is merely illustrative and does not limit the scope of protection of the present invention. In practical applications, technicians in this field can select part or all of it according to actual needs to achieve the purpose of the embodiment scheme, and no limitation is made here.

[0100] In addition, for technical details not fully described in this embodiment, please refer to the group purchase product recommendation method provided in any embodiment of the present invention, and will not be repeated here.

[0101] In one embodiment, the group purchase product recommendation device further includes a community division module;

[0102] The community division module is configured to determine the location information corresponding to each group purchasing user in the group purchasing record of each product; read the initial community division grid, and determine the initial community corresponding to the location information based on the initial community division grid; perform clustering based on the group purchasing record and the corresponding multiple initial communities to obtain a target community division grid;

[0103] The determining module 20 is further configured to determine the community grid where the current location is located according to the target community grid division; and determine the community corresponding to the target terminal based on the community grid.

[0104] In one embodiment, the construction module 30 is further configured to obtain portrait features from the user information, the purchase records, and the browsing records; and construct a user portrait corresponding to the target terminal based on the portrait features.

[0105] In one embodiment, the recommendation module 40 is further used to filter all group-purchased products based on the community and the several product types to obtain several group-purchased products; sort the several group-purchased products to obtain a product recommendation order; and recommend suitable group-purchased products to the target terminal according to the product recommendation order.

[0106] In one embodiment, the recommendation module 40 is further used to obtain the graphic and text description information, purchase volume and praise rate corresponding to the group-purchased products; determine the product score corresponding to each of the group-purchased products based on the graphic and text description information, the purchase volume and the praise rate; and sort the group-purchased products based on the product score to obtain a product recommendation order.

[0107] In one embodiment, the group purchase product recommendation device further includes a message push module;

[0108] The message push module is used to push the corresponding published life circle content to the target terminal based on the community and the user portrait.

[0109] In one embodiment, the message push module is also used to determine a number of corresponding seller users based on the community; determine a number of buyer users corresponding to the user portrait, wherein the similarity between the target user portrait corresponding to the buyer user and the user portrait is greater than a preset threshold; obtain the published life circle content corresponding to the several seller users and the several buyer users, and push it to the target terminal.

[0110] In addition, it should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or system comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or system. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or system comprising the element.

[0111] The serial numbers of the above embodiments of the present invention are for description only and do not represent the advantages or disadvantages of the embodiments.

[0112] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, or of course by hardware, but in many cases the former is a better embodiment. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product is stored in a storage medium (such as a read-only memory (ROM) / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for enabling a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0113] The above are only preferred embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention description and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for recommending group-buying products, characterized in that: The group purchase commodity recommendation method includes: Upon receiving an access request from a target terminal, obtaining the current location, user information, purchase history, and browsing history corresponding to the target terminal; Determining a community corresponding to the target terminal according to the current location; Constructing a user profile corresponding to the target terminal based on the user information, the purchase history, and the browsing history; Determine several product types corresponding to the user profile; recommending suitable group-buying products to the target terminal based on the community and the multiple product types; Before determining the community corresponding to the target terminal according to the current location, the method further includes: Determine the location information corresponding to each group purchasing user in the group purchasing record of each product; Reading an initial community division grid, and determining an initial community corresponding to the location information according to the initial community division grid; Clustering is performed based on the group purchase records and the corresponding multiple initial communities to obtain a target community division grid; The step of clustering the group purchase records and the corresponding multiple initial communities to obtain a target community division grid includes: grouping multiple initial communities with a correlation greater than a preset correlation threshold into the same target community to obtain an adjusted target community division grid; The determining, according to the current location, a community corresponding to the target terminal includes: Determine the community grid where the current location is located according to the target community grid division; The community corresponding to the target terminal is determined based on the community grid, including a plurality of initial communities with high correlation.

2. The group purchase product recommendation method according to claim 1, wherein: The constructing a user profile corresponding to the target terminal according to the user information, the purchase record, and the browsing record includes: Obtaining portrait features from the user information, the purchase history, and the browsing history; A user portrait corresponding to the target terminal is constructed based on the portrait features.

3. The group purchase product recommendation method according to claim 1, wherein: The recommending suitable group-buying products to the target terminal based on the community and the multiple product types includes: Filtering all group-purchased products based on the community and the multiple product types to obtain multiple group-purchased products; Sorting the group-purchased products to obtain a recommended order of products; Recommend suitable group-buying products to the target terminal according to the product recommendation order.

4. The group purchase product recommendation method according to claim 3, wherein: The step of sorting the group-purchased products to obtain a recommended order of products includes: Obtaining graphic and text description information, purchase volume, and favorable review rate corresponding to the group-purchased products; Determine a product rating corresponding to each of the group-purchased products based on the graphic description information, the purchase volume, and the favorable review rate; The group-purchased products are sorted based on the product ratings to obtain a product recommendation order.

5. The group purchase product recommendation method according to claim 1, wherein: After constructing the user profile corresponding to the target terminal according to the user information, the purchase history, and the browsing history, the method further includes: The corresponding published life circle content is pushed to the target terminal based on the community and the user portrait.

6. The group purchase product recommendation method according to claim 5, wherein: The pushing corresponding published life circle content to the target terminal based on the community and the user portrait includes: Determining a number of corresponding seller users based on the community; Determine a number of buyer users corresponding to the user profile, wherein the similarity between the target user profile corresponding to the buyer user and the user profile is greater than a preset threshold; The published life circle contents corresponding to the plurality of seller users and the plurality of buyer users are obtained and pushed to the target terminal.

7. A group purchase product recommendation device, characterized in that: The group purchase commodity recommendation device includes: An acquisition module, configured to acquire the current location, user information, purchase history, and browsing history of a target terminal upon receiving an access request from the target terminal; A determination module, configured to determine a community corresponding to the target terminal according to the current location; A construction module, configured to construct a user profile corresponding to the target terminal based on the user information, the purchase record, and the browsing record; The determination module is further configured to determine a number of commodity types corresponding to the user portrait; A recommendation module, configured to recommend suitable group-buying products to the target terminal based on the community and the multiple product types; The group purchase product recommendation device further includes a community division module; The community division module is configured to determine the location information corresponding to each group purchasing user in the group purchasing record of each commodity; read the initial community division grid, and determine the initial community corresponding to the location information based on the initial community division grid; cluster the group purchasing records and the corresponding multiple initial communities to obtain a target community division grid; the step of clustering the group purchasing records and the corresponding multiple initial communities to obtain the target community division grid includes: grouping multiple initial communities with a correlation greater than a preset correlation threshold into the same target community to obtain an adjusted target community division grid; The determination module is further configured to determine the community grid where the current location is located according to the target community grid division; and determine the community corresponding to the target terminal based on the community grid, including multiple initial communities with high correlation.

8. A group purchase product recommendation device, characterized in that: The device includes: a memory, a processor, and a group-buying commodity recommendation program stored in the memory and executable on the processor, wherein the group-buying commodity recommendation program is configured to implement the group-buying commodity recommendation method according to any one of claims 1 to 6.

9. A storage medium, characterized in that: The storage medium stores a group-buying product recommendation program, which, when executed by a processor, implements the group-buying product recommendation method according to any one of claims 1 to 6.

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