A community dating method, system, computer device, and storage medium

Abstract

The present invention relates to a community dating method, system, computer device, and storage medium. The key points of the technical solution are as follows: The method includes: receiving and storing the first dating request information of the first user; generating a first consumption page according to the first dating request information; receiving the first consumption information of the first consumption page and launching a storage mechanism; receiving the recycling location information of the storage mechanism, and matching the recycling location information of the storage mechanism with the first dating request information; receiving the second dating request information of the second user; generating a second consumption page according to the second dating request information; receiving the second consumption information of the second consumption page, and matching the storage mechanism corresponding to the recycling location information from the database according to the second dating request information; launching the storage mechanism, and sending a prompt message to the first user according to the recycling location information of the storage mechanism; This application enables users to complete dating in real life.

Description

Technical Field

[0001] The present invention relates to the technical field of social systems, and more specifically, it relates to a community dating method, system, computer device, and storage medium. Background Art

[0002] Traditional social systems used on handheld terminals all adopt a manually triggered method to search for users within a certain range, and use text information, intermittent voice, or video images as the carrier of social content. Due to the large number of users in the social network, it is difficult for users to find suitable social partners from the social network.

[0003] Existing friend recommendation methods recommend friends based on user characteristics. However, user characteristics can be divided into various types of users according to different dimensions, and different types of users have different social needs. Existing friend recommendation methods cannot accurately identify the social needs of users, resulting in a low degree of fit between the recommended friends and the social needs of the user, making it difficult for users to find suitable social partners among the massive users in the social network.

[0004] Moreover, the friend recommendation methods in social networks have great limitations, that is, they are always virtual network communications and cannot enter real life, so there is still room for improvement. Summary of the Invention

[0005] Aiming at the deficiencies of the existing technology, the purpose of the present invention is to provide a community dating method, system, computer device, and storage medium, which have the advantage of enabling users to complete dating in real life.

[0006] The above technical objective of the present invention is achieved through the following technical solutions: A community dating method includes:

[0007] Receiving and storing the first dating request information of the first user;

[0008] Generating a first consumption page according to the first dating request information;

[0009] Receiving the first consumption information of the first consumption page and launching a storage mechanism;

[0010] Receiving the recycling location information of the storage mechanism, matching the recycling location information of the storage mechanism with the first dating request information, and storing it in the database;

[0011] Receiving the second dating request information of the second user;

[0012] Generating a second consumption page according to the second dating request information;

[0013] Receive the second consumption information of the second consumption page, and match the storage institutions corresponding to the recycling location information from the database according to the second friend-making request information;

[0014] Push out the storage institutions corresponding to the recycling location information, and send a prompt message to the first user according to the recycling location information of the storage institutions.

[0015] Optionally, the first friend-making request information includes: the account information of the first user, the contact information of the first user, the gender information of the first user, the expected friend-making gender information of the first user, the interest information of the first user, and the expected friend-making interest information of the first user.

[0016] Optionally, the second friend-making request information includes: the account information of the second user, the gender information of the second user, the expected friend-making gender information of the second user, the interest information of the second user, and the expected friend-making interest information of the second user.

[0017] Optionally, the matching of the storage institutions corresponding to the recycling location information from the database according to the second friend-making request information includes:

[0018] Extract a number of first friend-making request information of the gender information of the corresponding first user from the database according to the expected friend-making gender information of the second user to obtain a first data set;

[0019] Extract a number of first friend-making request information of the expected friend-making gender information of the corresponding first user from the first data set according to the gender information of the second user to obtain a second data set;

[0020] Perform semantic recognition on the interest information of the second user and the expected friend-making interest information of the first user in a number of first friend-making request information in the second data set, and calculate the first matching degree between the interest information of the second user and the expected friend-making interest information of the first user;

[0021] Perform semantic recognition on the expected friend-making interest information of the second user and the interest information of the first user in a number of first friend-making request information in the second data set, and calculate the second matching degree between the expected friend-making interest information of the second user and the interest information of the first user;

[0022] Calculate the matching degree between the second friend-making request information and all the first friend-making request information in the second data set according to the first matching degree and the second matching degree, and use the storage institution corresponding to the first friend-making request information with the highest matching degree as the storage institution matching the second friend-making request information.

[0023] Optionally, the semantic recognition of the expected friendship interest information of the first user for the interest information of the second user and several first friendship request information in the second dataset, and calculating the first matching degree between the interest information of the second user and the expected friendship interest information of the first user, includes:

[0024] Performing semantic recognition on the interest information of the second user to obtain the interest feature words of the second user;

[0025] Performing semantic recognition on the expected friendship interest information of the first user for several first friendship request information in the second dataset to obtain several expected interest feature words of the first user;

[0026] Performing similarity matching between the interest feature words of the second user and several expected interest feature words of the first user to obtain the first matching degree between the interest information of the second user and the expected friendship interest information of the first user.

[0027] Optionally, the semantic recognition of the expected friendship interest information of the second user and the interest information of the first user for several first friendship request information in the second dataset, and calculating the second matching degree between the expected friendship interest information of the second user and the interest information of the first user, includes:

[0028] Performing semantic recognition on the expected friendship interest information of the second user to obtain the expected interest feature words of the second user;

[0029] Performing semantic recognition on the interest information of the first user for several first friendship request information in the second dataset to obtain several interest feature words of the first user;

[0030] Performing similarity matching between the expected interest feature words of the second user and several interest feature words of the first user to obtain the second matching degree between the interest information of the second user and the expected friendship interest information of the first user.

[0031] Optionally, the calculating of the matching degree between the second friendship request information and all the first friendship request information in the second dataset according to the first matching degree and the second matching degree includes:

[0032] Setting the weight of the first matching degree to 35% and the weight of the second matching degree to 65%;

[0033] Performing weighted average on the first matching degree and the second matching degree according to the weights of the first matching degree and the second matching degree to obtain the matching degree between the second friendship request information and all the first friendship request information in the second dataset.

[0034] A community friendship system, including: a first request receiving module, configured to receive and store the first friendship request information of the first user;

[0035] The first consumption generation module is used to generate a first consumption page according to the first friend-making request information;

[0036] The first separation module is used to receive the first consumption information of the first consumption page and launch a storage mechanism;

[0037] The matching and positioning module is used to receive the recycling location information of the storage mechanism, match the recycling location information of the storage mechanism with the first friend-making request information, and store it in the database;

[0038] The second request receiving module is used to receive the second friend-making request information of the second user;

[0039] The second consumption generation module is used to generate a second consumption page according to the second friend-making request information;

[0040] The information matching module is used to receive the second consumption information of the second consumption page and match the storage mechanism with the corresponding recycling location information from the database according to the second friend-making request information;

[0041] The second separation module is used to launch the storage mechanism with the corresponding recycling location information and send a prompt message to the first user according to the recycling location information of the storage mechanism.

[0042] A computer device includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the steps of the above method are implemented.

[0043] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above method are implemented.

[0044] In summary, the present invention has the following beneficial effects: First, the first user fills in the first friend-making request information through a mobile device such as a mobile phone; subsequently, a first consumption page pops up. After the first user completes the payment, a mobile storage bin pops up. The first user can place gifts such as lipsticks and jewelry, etc., small items, or place a note with their own friend-making concept in the mobile storage bin; then the first user can store the mobile storage bin in any storage hole on the intelligent shared locker. At this time, the intelligent shared locker receives the recycling position information of the storage mechanism and records the position of the storage hole, making the storage hole match the first user; when the second user needs to make friends, they can choose to select a friend-making object from the existing database. Therefore, the second user scans the QR code on the intelligent shared locker through a mobile device such as a mobile phone to fill in the second friend-making request information. Among them, the second friend-making request information includes: the account information of the second user, the gender information of the second user, the expected friend-making gender information of the second user, the interest information of the second user, and the expected friend-making interest information of the second user; a second consumption page pops up on the intelligent shared locker. After the second user completes the payment, the intelligent shared locker matches the second friend-making request information with the first friend-making request information in the database and pops up the mobile storage bin at the storage hole corresponding to the first friend-making request information with the highest matching degree. The second user can take away the mobile storage bin. At the same time, the mobile phone of the first user will receive a message that the mobile storage bin has been taken away. At the same time, the intelligent shared locker will send the matching result to the first user and the second user respectively, and the matching can be completed. Since the first user and the second user make friends through the same intelligent shared locker, the distance between the first user and the second user can be shortened, enabling the first user and the second user to make friends in real life. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 is a schematic flow chart of the present invention;

[0046] Figure 2 is a structural block diagram during the assembly of the present invention;

[0047] Figure 3 is an internal structure diagram of a computer device in an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0048] In order to make the objectives, features, and advantages of the present invention more obvious and understandable, the following provides a detailed description of the specific embodiments of the present invention with reference to the accompanying drawings. Several embodiments of the present invention are shown in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein.

[0049] In the present invention, unless otherwise clearly defined and limited, terms such as "installation", "connection", "linkage", "fixation" shall be understood in a broad sense. For example, it may be a fixed connection, a detachable connection, or an integral connection; it may be a mechanical connection or an electrical connection; it may be a direct connection or an indirect connection through an intermediate medium, and it may be the communication inside two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances. The terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features.

[0050] In the present invention, unless otherwise clearly defined and limited, that the first feature is "above" or "below" the second feature may include the direct contact between the first and second features, or may include the contact between the first and second features not directly but through additional features therebetween. Moreover, that the first feature is "above", "over" and "on" the second feature includes that the first feature is directly above and obliquely above the second feature, or merely means that the horizontal height of the first feature is higher than that of the second feature. That the first feature is "under", "beneath" and "underneath" the second feature includes that the first feature is directly below and obliquely below the second feature, or merely means that the horizontal height of the first feature is lower than that of the second feature. The terms "vertical", "horizontal", "left", "right", "above", "below" and similar expressions are only for the purpose of illustration, rather than indicating or implying that the indicated device or element must have a specific orientation, be constructed and operated in a specific orientation, and thus cannot be understood as a limitation to the present invention.

[0051] The present invention will be described in detail below with reference to the accompanying drawings and embodiments.

[0052] The present invention provides a community dating method, as Figure 1 shown, including:

[0053] Step 100: Receive and store the first dating request information of the first user;

[0054] Step 200: Generate a first consumption page according to the first dating request information;

[0055] Step 300: Receive the first consumption information of the first consumption page and launch a storage mechanism;

[0056] Step 400: Receive the recycling location information of the storage mechanism, match the recycling location information of the storage mechanism with the first dating request information, and store it in the database;

[0057] Step 500: Receive the second dating request information of the second user;

[0058] Step 600: Generate a second consumption page according to the second friend-making request information;

[0059] Step 700: Receive the second consumption information of the second consumption page, and match a storage institution with corresponding recycling location information from the database according to the second friend-making request information;

[0060] Step 800: Promote the storage institution with corresponding recycling location information, and send a prompt message to the first user according to the recycling location information of this storage institution.

[0061] In practical applications, the first user seeking to make friends scans the QR code set on the intelligent shared storage locker located by the roadside or in indoor stores through a mobile device such as a mobile phone to fill in the first friend-making request information. The intelligent shared storage locker is provided with a number of storage holes, and a mobile storage bin is detachably connected in the storage hole. The first friend-making request information includes: the account information of the first user, the contact information of the first user, the gender information of the first user, the expected friend-making gender information of the first user, the interest information of the first user, and the expected friend-making interest information of the first user. Subsequently, a first consumption page pops up on the intelligent shared storage locker. After the first user completes the payment, the intelligent shared storage locker randomly pops up a mobile storage bin. The first user can place gifts such as lipsticks and small items like jewelry in the mobile storage bin, or place a note with their own friend-making concept. Then the first user can store the mobile storage bin in any of the storage holes on the intelligent shared storage locker. At this time, the intelligent shared storage locker receives the recycling position information of the storage mechanism, records the position of the storage hole, and matches the storage hole with the first user. At the same time, the first friend-making request information is correspondingly displayed on the friend-making display page. When the second user needs to make friends, they can choose to select the storage mechanism at any position in the intelligent shared storage locker from the friend-making display page. After clicking on any storage mechanism, the friend-making display page will display the first friend-making request information corresponding to the storage mechanism. The second user can select each storage mechanism according to their own interest level and make a payment after selection. Subsequently, the intelligent shared storage locker pops up the storage mechanism at the corresponding position. The second user can also scan the QR code on the intelligent shared storage locker through a mobile device such as a mobile phone to fill in the second friend-making request information. The second friend-making request information includes: the account information of the second user, the gender information of the second user, the expected friend-making gender information of the second user, the interest information of the second user, and the expected friend-making interest information of the second user. A second consumption page pops up on the intelligent shared storage locker. After the second user completes the payment, the intelligent shared storage locker matches the second friend-making request information with the first friend-making request information in the database and pops up the mobile storage bin at the storage hole corresponding to the first friend-making request information with the highest matching degree. The second user can take away the mobile storage bin. At the same time, the first user's mobile phone will receive a message that the mobile storage bin has been taken away. At the same time, the intelligent shared storage locker will send the matching result to the first user and the second user respectively, and the matching can be completed. Since the first user and the second user make friends through the same intelligent shared storage locker, the distance between the first user and the second user can be shortened, enabling the first user and the second user to make friends in real life.

[0062] Specifically, users can fill in their personal information through the intelligent shared locker and WeChat mini-program, and access the community dating method of this application. The intelligent shared locker can divert the customer source to the corresponding WeChat mini-program. When matching is completed in the WeChat mini-program, the WeChat mini-program will divert the customer source to the corresponding intelligent shared locker. Moreover, the WeChat mini-program has navigation information for all intelligent shared lockers, i.e., physical stores, within a certain distance of the user. The user can move to any intelligent shared locker or physical store according to the navigation information. Among them, the intelligent shared lockers of this application can be set by the roadside or centrally in physical stores. That is, the customer source can be diverted from the intelligent shared lockers and WeChat mini-program to the physical store to realize the monetization conversion of the accurate customer source. When customers pass by the physical store, they will also be attracted, thus accessing the intelligent shared locker and WeChat mini-program, realizing the diversion of the physical store to the intelligent shared locker and WeChat mini-program. Therefore, it can realize the diversion closed-loop of the intelligent shared locker, WeChat mini-program and physical store, thereby effectively increasing the customer source.

[0063] Optionally, the storage institution that matches the corresponding recycling location information from the database according to the second dating request information includes:

[0064] Extracting a number of first dating request information of the gender information of the corresponding first user from the database according to the expected dating gender information of the second user to obtain a first data set;

[0065] Extracting a number of first dating request information of the expected dating gender information of the corresponding first user from the first data set according to the gender information of the second user to obtain a second data set;

[0066] Performing semantic recognition on the interest information of the second user and the expected dating interest information of the first user in a number of first dating request information in the second data set, and calculating the first matching degree between the interest information of the second user and the expected dating interest information of the first user;

[0067] Performing semantic recognition on the expected dating interest information of the second user and the interest information of the first user in a number of first dating request information in the second data set, and calculating the second matching degree between the expected dating interest information of the second user and the interest information of the first user;

[0068] Calculating the matching degree between the second dating request information and all first dating request information in the second data set according to the first matching degree and the second matching degree, and taking the storage institution corresponding to the first dating request information with the highest matching degree as the storage institution matching the second dating request information.

[0069] In practical applications, first determine the genders of the first user and the second user and their expected genders for making friends. After matching, match the interests of the first user and the second user and their expected interests for making friends, and calculate the matching degree accordingly. The intelligent shared locker makes a threshold judgment on the matching degree. When the matching degree exceeds the preset threshold, the storage institution corresponding to the recycling location information of the first user with the highest matching degree is used as the storage institution that matches the second friend-making request information of the second user. Among them, the preset threshold is set to 80%.

[0070] Furthermore, the semantic recognition of the interest information of the second user and the expected friend-making interest information of the first user in several first friend-making request information in the second dataset, and the calculation of the first matching degree between the interest information of the second user and the expected friend-making interest information of the first user, include:

[0071] Perform semantic recognition on the interest information of the second user to obtain the interest feature words of the second user;

[0072] Perform semantic recognition on the expected friend-making interest information of the first user in several first friend-making request information in the second dataset to obtain several expected interest feature words of the first user;

[0073] Perform similarity matching between the interest feature words of the second user and several expected interest feature words of the first user to obtain the first matching degree between the interest information of the second user and the expected friend-making interest information of the first user.

[0074] In practical applications, the interest information and the expected friend-making interest information can be standardized terms set in advance, or can be manually filled in by the first user and the second user. Therefore, semantic recognition needs to be performed on the interest information and the expected friend-making interest information to obtain interest feature words and expected interest feature words with the same semantics, and similarity calculation is performed based on the interest feature words and the expected interest feature words, and then the first matching degree between the interest information of the second user and the expected friend-making interest information of the first user can be obtained.

[0075] Furthermore, the semantic recognition of the expected friend-making interest information of the second user and the interest information of the first user in several first friend-making request information in the second dataset, and the calculation of the second matching degree between the expected friend-making interest information of the second user and the interest information of the first user, include:

[0076] Perform semantic recognition on the expected friend-making interest information of the second user to obtain the expected interest feature words of the second user;

[0077] Perform semantic recognition on the interest information of the first user in several first friend-making request information in the second dataset to obtain several interest feature words of the first user;

[0078] Performing similarity matching between the expected interest feature words of the second user and the interest feature words of several first users to obtain the second matching degree between the interest information of the second user and the expected friendship interest information of the first user.

[0079] In practical applications, the interest information and the expected friendship interest information can be pre-set standard terms, or can be manually filled in by the first user and the second user. Therefore, semantic recognition needs to be performed on the interest information and the expected friendship interest information to obtain interest feature words and expected interest feature words with the same semantics, and similarity calculation is performed based on the interest feature words and the expected interest feature words, so as to obtain the second matching degree between the interest information of the first user and the expected friendship interest information of the second user.

[0080] Further, calculating the matching degree between the second friendship request information and all the first friendship request information in the second dataset based on the first matching degree and the second matching degree includes:

[0081] Setting the weight of the first matching degree to 35% and the weight of the second matching degree to 65%;

[0082] Performing weighted averaging on the first matching degree and the second matching degree according to the weights of the first matching degree and the second matching degree to obtain the matching degree between the second friendship request information and all the first friendship request information in the second dataset.

[0083] In practical applications, in order to meet the matching degree of the second user, the weights of the first matching degree and the second matching degree are set. Since the second matching degree is the similarity between the expected friendship interest of the second user and the interest of the first user, it can better reflect the friendship interest of the second user. Setting the weight of the second matching degree higher can improve the user experience of the second user.

[0084] As Figure 2 shown, the present invention also provides a community friendship system, including:

[0085] A first request receiving module 10, configured to receive and store the first friendship request information of the first user;

[0086] A first consumption generating module 20, configured to generate a first consumption page according to the first friendship request information;

[0087] A first separation module 30, configured to receive the first consumption information of the first consumption page and push out a storage mechanism;

[0088] A matching and positioning module 40, configured to receive the recycling position information of the storage mechanism, match the recycling position information of the storage mechanism with the first friendship request information, and store it in a database;

[0089] The second request receiving module 50 is configured to receive the second friend-making request information of the second user;

[0090] The second consumption generating module 60 is configured to generate a second consumption page according to the second friend-making request information;

[0091] The information matching module 70 is configured to receive the second consumption information of the second consumption page, and match a storage institution corresponding to the recycling location information from the database according to the second friend-making request information;

[0092] The second separation module 80 is configured to launch the storage institution corresponding to the recycling location information, and send a prompt message to the first user according to the recycling location information of the storage institution.

[0093] Further, the information matching module 40 includes:

[0094] The first data screening unit is configured to extract a plurality of first friend-making request information of the corresponding first user's gender information from the database according to the expected friend-making gender information of the second user, and obtain a first data set;

[0095] The second data screening unit is configured to extract a plurality of first friend-making request information of the corresponding first user's expected friend-making gender information from the first data set according to the gender information of the second user, and obtain a second data set;

[0096] The first information matching unit is configured to perform semantic recognition on the interest information of the second user and the expected friend-making interest information of the first user in a plurality of first friend-making request information in the second data set, and calculate a first matching degree between the interest information of the second user and the expected friend-making interest information of the first user;

[0097] The second information matching unit is configured to perform semantic recognition on the expected friend-making interest information of the second user and the interest information of the first user in a plurality of first friend-making request information in the second data set, and calculate a second matching degree between the expected friend-making interest information of the second user and the interest information of the first user;

[0098] The matching degree calculation unit is configured to calculate the matching degree between the second friend-making request information and all the first friend-making request information in the second data set according to the first matching degree and the second matching degree, and use the storage institution corresponding to the first friend-making request information with the highest matching degree as the storage institution matching the second friend-making request information.

[0099] Further, the first information matching unit includes:

[0100] The first semantic recognition unit is configured to perform semantic recognition on the interest information of the second user to obtain the interest feature words of the second user;

[0101] A second semantic recognition unit, configured to perform semantic recognition on the expected dating interest information of the first users in a number of first dating request messages in the second dataset, so as to obtain a number of expected interest feature words of the first users;

[0102] A first similarity matching unit, configured to perform similarity matching between the interest feature words of the second user and the expected interest feature words of a number of first users, so as to obtain a first matching degree between the interest information of the second user and the expected dating interest information of the first users.

[0103] Further, the second information matching unit includes:

[0104] A third semantic recognition unit, configured to perform semantic recognition on the expected dating interest information of the second user, so as to obtain the expected interest feature words of the second user;

[0105] A fourth semantic recognition unit, configured to perform semantic recognition on the interest information of the first users in a number of first dating request messages in the second dataset, so as to obtain a number of interest feature words of the first users;

[0106] A second similarity matching unit, configured to perform similarity matching between the expected interest feature words of the second user and the interest feature words of a number of first users, so as to obtain a second matching degree between the interest information of the second user and the expected dating interest information of the first users.

[0107] Further, the matching degree calculation unit includes:

[0108] A weight assignment unit, configured to set the weight of the first matching degree to 35% and the weight of the second matching degree to 65%;

[0109] A weighted average unit, configured to perform a weighted average on the first matching degree and the second matching degree according to the weights of the first matching degree and the second matching degree, so as to obtain the matching degree between the second dating request message and all the first dating request messages in the second dataset.

[0110] For the specific limitations of a community dating system, reference may be made to the limitations on a community dating method in the foregoing text, which will not be elaborated herein. Each module in the foregoing community dating system may be implemented in whole or in part by software, hardware, and their combination. The foregoing modules may be embedded in or independent of a processor in a computer device in the form of hardware, or may be stored in a memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to the foregoing modules.

[0111] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as Figure 3As shown in the figure. The computer device includes a processor, a memory, a network interface, and a database connected through a device bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating device, a computer program, and a database. The internal memory provides an environment for the operation of the operating device and the computer program in the non-volatile storage medium. When the computer program is executed by the processor, it realizes a community dating method.

[0112] Those skilled in the art can understand that Figure 3 the structure shown in the figure is only a block diagram of some structures related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0113] In one embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory. When the processor executes the computer program, the following steps are realized: receiving and storing the first dating request information of the first user;

[0114] generating a first consumption page according to the first dating request information;

[0115] receiving the first consumption information of the first consumption page and launching a storage mechanism; [[ID=I5]]

[0116] receiving the recycling position information of the storage mechanism, matching the recycling position information of the storage mechanism with the first dating request information, and storing it in the database;

[0117] receiving the second dating request information of the second user;

[0118] generating a second consumption page according to the second dating request information;

[0119] receiving the second consumption information of the second consumption page, and matching the storage mechanism with the corresponding recycling position information from the database according to the second dating request information;

[0120] launching the storage mechanism with the corresponding recycling position information, and sending a prompt message to the first user according to the recycling position information of the storage mechanism.

[0121] In one embodiment, the first dating request information includes: the account information of the first user, the contact information of the first user, the gender information of the first user, the expected dating gender information of the first user, the interest information of the first user, and the expected dating interest information of the first user.

[0122] In one embodiment, the second friend-making request information includes: the account information of the second user, the gender information of the second user, the expected friend-making gender information of the second user, the interest information of the second user, and the expected friend-making interest information of the second user.

[0123] In one embodiment, the storage institution that matches the corresponding recycling location information from the database according to the second friend-making request information includes:

[0124] Extracting a number of first friend-making request information of the gender information of the corresponding first user from the database according to the expected friend-making gender information of the second user to obtain a first data set;

[0125] Extracting a number of first friend-making request information of the expected friend-making gender information of the corresponding first user from the first data set according to the gender information of the second user to obtain a second data set;

[0126] Performing semantic recognition on the interest information of the second user and the expected friend-making interest information of the first user in a number of first friend-making request information in the second data set, and calculating the first matching degree between the interest information of the second user and the expected friend-making interest information of the first user;

[0127] Performing semantic recognition on the expected friend-making interest information of the second user and the interest information of the first user in a number of first friend-making request information in the second data set, and calculating the second matching degree between the expected friend-making interest information of the second user and the interest information of the first user;

[0128] Calculating the matching degree between the second friend-making request information and all the first friend-making request information in the second data set according to the first matching degree and the second matching degree, and taking the storage institution corresponding to the first friend-making request information with the highest matching degree as the storage institution matching the second friend-making request information.

[0129] In one embodiment, the performing semantic recognition on the interest information of the second user and the expected friend-making interest information of the first user in a number of first friend-making request information in the second data set, and calculating the first matching degree between the interest information of the second user and the expected friend-making interest information of the first user includes:

[0130] Performing semantic recognition on the interest information of the second user to obtain the interest feature words of the second user;

[0131] Performing semantic recognition on the expected friend-making interest information of the first user in a number of first friend-making request information in the second data set to obtain a number of expected interest feature words of the first user;

[0132] Performing similarity matching between the interest feature words of the second user and a number of expected interest feature words of the first user to obtain the first matching degree between the interest information of the second user and the expected friend-making interest information of the first user.

[0133] In one embodiment, semantic recognition is performed on the expected friend-making interest information of the second user and the interest information of the first user in several first friend-making request messages in the second dataset, and a second matching degree between the expected friend-making interest information of the second user and the interest information of the first user is calculated, including:

[0134] Perform semantic recognition on the expected friend-making interest information of the second user to obtain the expected interest feature words of the second user;

[0135] Perform semantic recognition on the interest information of the first user in several first friend-making request messages in the second dataset to obtain several interest feature words of the first user;

[0136] Perform similarity matching between the expected interest feature words of the second user and several interest feature words of the first user to obtain a second matching degree between the interest information of the second user and the expected friend-making interest information of the first user.

[0137] In one embodiment, calculating the matching degree between the second friend-making request message and all the first friend-making request messages in the second dataset according to the first matching degree and the second matching degree includes:

[0138] Set the weight of the first matching degree to 35% and the weight of the second matching degree to 65%;

[0139] Perform weighted averaging on the first matching degree and the second matching degree according to the weights of the first matching degree and the second matching degree to obtain the matching degree between the second friend-making request message and all the first friend-making request messages in the second dataset.

[0140] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium used in the embodiments provided in the present application can include non-volatile and / or volatile memories. Non-volatile memories can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memories can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0141] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0142] The above description is only a preferred embodiment of the present invention. The protection scope of the present invention is not limited to the above embodiments. All technical solutions falling within the concept of the present invention belong to the protection scope of the present invention. It should be noted that for those of ordinary skill in the art in this technical field, several improvements and refinements made without departing from the principle of the present invention should also be regarded as within the protection scope of the present invention.

Claims

1. A community dating method, characterized in that, Including: Receiving and storing the first friend-making request information of the first user; Generating a first consumption page according to the first friend-making request information; Receiving the first consumption information of the first consumption page and launching a storage institution; Receiving the recycling location information of the storage institution, and matching the recycling location information of the storage institution with the first friend-making request information; Receiving the second friend-making request information of the second user; Generating a second consumption page according to the second friend-making request information; Receiving the second consumption information of the second consumption page, and matching the storage institution with the corresponding recycling location information from the database according to the second friend-making request information; Launching the storage institution with the corresponding recycling location information, and sending a prompt message to the first user according to the recycling location information of the storage institution; The first friend-making request information includes: the account information of the first user, the contact information of the first user, the gender information of the first user, the expected friend-making gender information of the first user, the interest information of the first user, and the expected friend-making interest information of the first user; The second friend-making request information includes: the account information of the second user, the gender information of the second user, the expected friend-making gender information of the second user, the interest information of the second user, and the expected friend-making interest information of the second user; The matching of the storage institution with the corresponding recycling location information from the database according to the second friend-making request information includes: Extracting a number of first friend-making request information of the corresponding gender information of the first user from the database according to the expected friend-making gender information of the second user to obtain a first data set; Extracting a number of first friend-making request information of the corresponding expected friend-making gender information of the first user from the first data set according to the gender information of the second user to obtain a second data set; Performing semantic recognition on the interest information of the second user and the expected friend-making interest information of the first user in a number of first friend-making request information in the second data set, and calculating the first matching degree between the interest information of the second user and the expected friend-making interest information of the first user; Performing semantic recognition on the expected friend-making interest information of the second user and the interest information of the first user in a number of first friend-making request information in the second data set, and calculating the second matching degree between the expected friend-making interest information of the second user and the interest information of the first user; Calculating the matching degree between the second friend-making request information and all the first friend-making request information in the second data set according to the first matching degree and the second matching degree, and taking the storage institution with the recycling location information corresponding to the first friend-making request information with the highest matching degree as the storage institution matching the second friend-making request information; Determining the genders and expected friend-making genders of the first user and the second user, matching the interests and expected friend-making interests of the first user and the second user after matching, and correspondingly calculating the matching degree. The intelligent shared locker makes a threshold judgment on the matching degree. When the matching degree exceeds the preset threshold, the storage institution with the recycling location information corresponding to the first user with the highest matching degree is taken as the storage institution matching the second friend-making request information of the second user.

2. The method according to claim 1, wherein Semantically identify the expected friendship interest information of the first user for the interest information of the second user and several first friendship request information in the second dataset, and calculate the first matching degree between the interest information of the second user and the expected friendship interest information of the first user, including: Semantically identify the interest information of the second user to obtain the interest characteristic words of the second user; Semantically identify the expected friendship interest information of the first user for several first friendship request information in the second dataset to obtain several expected interest characteristic words of the first user; Perform similarity matching between the interest characteristic words of the second user and several expected interest characteristic words of the first user to obtain the first matching degree between the interest information of the second user and the expected friendship interest information of the first user.

3. The method according to claim 2, wherein Semantically identify the expected friendship interest information of the second user and the interest information of the first user for several first friendship request information in the second dataset, and calculate the second matching degree between the expected friendship interest information of the second user and the interest information of the first user, including: Semantically identify the expected friendship interest information of the second user to obtain the expected interest characteristic words of the second user; Semantically identify the interest information of the first user for several first friendship request information in the second dataset to obtain several interest characteristic words of the first user; Perform similarity matching between the expected interest characteristic words of the second user and several interest characteristic words of the first user to obtain the second matching degree between the interest information of the second user and the expected friendship interest information of the first user.

4. The method according to claim 3, wherein The calculating the matching degree between the second friendship request information and all the first friendship request information in the second dataset according to the first matching degree and the second matching degree includes: Set the weight of the first matching degree to 35% and the weight of the second matching degree to 65%; Perform weighted averaging on the first matching degree and the second matching degree according to the weights of the first matching degree and the second matching degree to obtain the matching degree between the second friendship request information and all the first friendship request information in the second dataset.

5. A community dating system, characterized in that, Including: A first request receiving module, configured to receive and store the first friendship request information of the first user; The first friendship request information includes: the account information of the first user, the contact information of the first user, the gender information of the first user, the expected friendship gender information of the first user, the interest information of the first user, and the expected friendship interest information of the first user; A first consumption generating module, configured to generate a first consumption page according to the first friendship request information; A first separation module, configured to receive the first consumption information of the first consumption page and push out a storage mechanism; A matching and positioning module, configured to receive the recycling location information of the storage mechanism, match the recycling location information of the storage mechanism with the first friendship request information, and store it in a database; A second request receiving module, configured to receive the second friendship request information of the second user; the second friendship request information includes: the account information of the second user, the gender information of the second user, the expected friendship gender information of the second user, the interest information of the second user, and the expected friendship interest information of the second user; A second consumption generating module, configured to generate a second consumption page according to the second friendship request information; An information matching module, configured to receive second consumption information of a second consumption page, and match a storage institution corresponding to recycling location information from a database according to the second friend-making request information; A second separation module, configured to push out the storage institution corresponding to the recycling location information, and send a prompt message to the first user according to the recycling location information of the storage institution.

6. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, the steps of the method according to any one of claims 1 to 4 are implemented.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, the steps of the method according to any one of claims 1 to 4 are implemented.

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