Group recommendation method and device

Abstract

The embodiment of the present application discloses a group recommendation method and device, the method comprising: a first client receives a joining request from a second client, the joining request carries first information and a first position, the first position is the position of a graphic code scanned by the second client, and the first information is the house information of the advertisement where the graphic code is located; determining the target group of the second client according to the first information and the first position; in response to the joining request, sending second information to the second client, the second information including the account and / or link of the target group. The present application can save the time of real estate consultants in user management and operation by being able to recommend suitable groups to users, thereby improving their work efficiency and customer success conversion rate.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a group recommendation method and device. Background Art

[0002] At present, the real estate industry has entered a downward channel, and customer resources have become increasingly precious. More and more real estate companies have begun to use WeChat for Business to contact customers. Many companies still use the relatively inefficient WeChat for Business community operation plan, which requires customers to scan a code to join the group. This method requires real estate consultants to spend a lot of time adding users and recommend suitable properties to customers from a large number of properties. It requires a lot of manpower and material resources and is inefficient. Summary of the invention

[0003] The embodiments of the present application provide a group recommendation method and device, which can recommend suitable groups to users, thereby saving the time of real estate consultants in user management and operation, and improving their work efficiency and customer success conversion rate.

[0004] In a first aspect, an embodiment of the present application provides a group recommendation method, the method comprising:

[0005] receiving a joining request from a second client, the joining request carrying first information and a first position, the first position being a position of a graphic code scanned by the second client, the first information including first housing source information, the first housing source information being housing source information of an advertisement where the graphic code is located;

[0006] determining a target group of the second client according to the first information and the first location;

[0007] In response to the joining request, second information is sent to the second client, where the second information includes an account and / or a link of the target group.

[0008] In a second aspect, an embodiment of the present application provides a group recommendation device, the device comprising a processing unit and a transceiver unit, wherein:

[0009] The transceiver unit is configured to receive a joining request from a second client, the joining request carrying first information and a first position, the first position being a position of a graphic code scanned by the second client, the first information including first housing source information, and the first housing source information being housing source information of an advertisement where the graphic code is located;

[0010] The processing unit is configured to determine a target group of the second client according to the first information and the first location;

[0011] The transceiver unit is further configured to send second information to the second client in response to the joining request, where the second information includes an account number and / or a link of the target group.

[0012] In a third aspect, an embodiment of the present application provides a terminal device, comprising a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the program includes instructions for executing some or all of the steps described in the method described in the first aspect above.

[0013] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, which stores a computer program for electronic data exchange, wherein the computer program enables a computer to execute some or all of the steps described in the method described in the first aspect above.

[0014] In a fifth aspect, an embodiment of the present application provides a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute some or all of the steps described in the method described in the first aspect of the embodiment of the present application. The computer program product may be a software installation package.

[0015] The technical solution provided by the present application is that a first client receives a joining request from a second client, the joining request carries first information and a first position, the first position is the position of a graphic code scanned by the second client, and the first information is the house information of the advertisement where the graphic code is located; the target group of the second client is determined according to the first information and the first position; in response to the joining request, second information is sent to the second client, the second information includes the account and / or link of the target group. The present application can save the time of real estate consultants in user management and operation by recommending suitable groups to users, thereby improving their work efficiency and customer success conversion rate. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0017] Figure 1 is a schematic diagram of an exemplary application scenario provided by an embodiment of the present application;

[0018] Figure 2 It is a flowchart of a group recommendation method provided in an embodiment of the present application;

[0019] Figure 3 It is a block diagram of the functional units of a group recommendation device provided by an embodiment of the present application;

[0020] Figure 4 It is a structural diagram of a terminal device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0021] In order to help those skilled in the art better understand the technical solutions of the present application, the following is a clear and complete description of the technical solutions in the embodiments of the present application in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, not all embodiments. Based on the description of the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present application.

[0022] The terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, software, product, or device that includes a series of steps or units is not limited to the listed steps or units, but also includes steps or units that are not listed, or also includes other steps or units inherent to these processes, methods, products, or devices.

[0023] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0024] See also Figure 1 , Figure 1 This is an exemplary application scenario provided by the embodiment of the present application. The method provided by the embodiment of the present application can be applied to Figure 1 The scenario shown in FIG. 1 , wherein the method provided in the embodiment of the present application can be applied to Figure 1 In the first client 110 shown, group recommendation to the user is implemented.

[0025] like Figure 1As shown, the second client 120 can add a property consultant of a real estate company for consultation by scanning a graphic code in a house flyer, advertisement or poster. Specifically, the second client 120 sends a joining request to the first client by scanning the graphic code. After receiving the request, the first client 110 can determine the target group that meets the user's needs based on the information carried in the joining request. Then the first client 110 sends the account and / or link of the target group to the second client 120, so that the user can be recommended a suitable group to learn about the house information according to the user's needs, thereby improving the work efficiency of the property consultant and the customer success conversion rate. Of course, Figure 1 The number of second client 120 devices is schematically shown for ease of understanding only, but this should not constitute a limitation to the present application.

[0026] It should be noted that the above application scenarios are only shown for the purpose of facilitating the understanding of the present application, and the implementation of the present application is not limited in this respect. On the contrary, the implementation of the present application can be applied to any applicable scenario.

[0027] See also Figure 2 , Figure 2 A schematic diagram of a group recommendation method provided in an embodiment of the present application is applied to Figure 1 The first client shown. Figure 2 As shown, the method includes the following steps.

[0028] S210. Receive a joining request from a second client, the joining request carrying first information and a first position, the first position being the position of the graphic code scanned by the second client, the first information including first housing information, and the first housing information being the housing information of the advertisement where the graphic code is located.

[0029] In a specific implementation, in order to establish initial contact with customers as quickly as possible, the property consultant will embed the graphic code of his or her corporate WeChat, WeChat and other communication chat accounts in promotional materials such as flyers, advertisements, and posters. By scanning the graphic code in the promotional material, the user can send a joining request to the first client to request to add the property consultant's communication chat account with the graphic code.

[0030] In an embodiment of the present application, in order to enable the first client to understand the housing purchase needs of the user using the second client, the second client may carry the location information of the scanned promotional material and the housing information on the promotional material in the joining request, so that the first client can understand the user's geographical location based on the location information and understand the user's housing purchase needs based on the housing information.

[0031] S220: Determine a target group of the second client according to the first information and the first location.

[0032] In the present application, in response to a joining request sent by a second client, the first client may recommend a suitable group to the second client, so that the user can access more listings that meet his needs, thereby improving the customer success conversion rate.

[0033] Among them, the first client can configure the adding method of its communication chat software or application, that is, when the first client receives the joining request of the second client, it can directly accept the joining request without user operation and add the user account of the second client.

[0034] For example, when a first client adds a second client, the first client can automatically send a configured message to the second client. The message may include pre-edited welcome content, customer membership registration rules and / or a link to register as a member, etc., to guide customers to register as members, obtain member benefits, and enhance the connectivity between users and property consultants.

[0035] The house source information includes a second location, which is the geographical location of the house source.

[0036] Specifically, when promoting housing sources, the real estate company may describe at least one of the geographical location, apartment type, apartment area, house type, price range, etc. of the promoted housing sources in the promotional materials. Furthermore, the real estate company may store such information of the housing sources in the graphic code of the promotional materials, and when the second client scans the graphic code, the user account of the first client, the second location, and the housing source information may be obtained.

[0037] Optionally, determining the target group of the first client based on the first information and the first position includes: calculating a first distance, the first distance being the distance between the second position and the first position; screening out at least one candidate group from all groups of the first client, the service range of the candidate group being larger than a first range, the first range being a range centered on the first position or the second position and having the first distance as a radius; determining the user's housing demand based on the first information; calculating a matching degree between each candidate group in the at least one candidate group and the user's housing demand; and determining the candidate group corresponding to the maximum matching degree as the target group.

[0038] In a specific implementation, when the second client can send a joining request to the first client, it means that the user's activity range includes the range where the promotional material is located, and the user is interested in the advertised house. Therefore, this application can obtain the user's acceptable range of houses by calculating the first distance, and the user's housing purchase needs can be determined through the information of the house on the promotional material, and then the group whose service range is larger than the range with the first position or the second position as the center and the first distance as the radius can be determined as a candidate group. Then, according to the matching degree between the candidate group and the user's housing purchase needs, the candidate group with the largest matching degree is selected from the candidate group as the target group to provide the user with housing consultation services.

[0039] The user's housing purchase demand includes at least one of the following: apartment type, apartment area, house type, and price range.

[0040] Specifically, if the user requests to add a property consultant based on the graphic code on the promotional material, it means that the user is interested in the house on the promotional material, so the house information on the promotional material can be used as the user's housing demand. For example, if the promoted house is a second-hand house with one bedroom and one living room of 80 square meters, the user's housing demand can be determined as one bedroom and one living room, about 80 square meters, and second-hand house.

[0041] Optionally, the calculating the matching degree between each candidate group in the at least one candidate group and the user's housing demand includes: acquiring label information of the at least one candidate group to obtain at least one label information; determining the priority of the apartment type, the apartment area, the house type and the price range according to the characteristics of the housing source; calculating the quantity matching degree and target similarity between each label information in the at least one label information and the user's housing demand according to the priority level; and calculating the matching degree of each candidate group according to the quantity matching degree and the target similarity.

[0042] In this application, the first client can pre-label the group according to the housing sources provided by the group to the user. For example, when the group provides second-hand housing information to the user, the label information of the group may include second-hand housing. When each housing source is promoted and sold, the real estate company will promote some characteristics of the housing source as the main selling point, such as school district housing, high-end housing, low price, large floor area, etc. The first client can determine the priority of the floor type, floor area, house type and price range in the housing source information according to the main selling point of the housing source, so that the real estate customer can recommend the housing source according to the user's most important needs, thereby improving its work efficiency and customer success conversion rate.

[0043] Among them, the first client obtains the label information pre-marked on each candidate group. Then, according to the priority order of the user's housing purchase needs, the label information of each candidate group is matched with the apartment type, apartment area, house type and price range, and the matching degree of each label information with the user's housing purchase needs is calculated. The quantity matching degree is used to represent the number of matches between the label information and the apartment type, apartment area, house type and price range. The larger the quantity matching degree, the more the candidate group meets the user's needs. The quantity matching degree can be expressed as: Where N is the number of users' housing purchase demands, and α i is the priority level of the i-th user's housing demand, and γ is used to indicate whether the label information matches the i-th user's housing demand. When the label information includes the i-th user's housing demand, r takes 1, otherwise it takes 0.

[0044] Furthermore, the target similarity is used to represent the similarity between the label information and each user's housing purchase demand. For example, the label information includes commercial housing, and the housing type of the user's housing purchase demand is second-hand housing. Since commercial housing can include second-hand housing, it can be considered that the label information and the housing type of the user's housing purchase demand are 50% similar. For another example, the label information includes a one-bedroom and one-living room, and the housing area of ​​the user's housing purchase demand is 40 square meters. Since the area of ​​a standard one-bedroom and one-living room is 40 square meters, it can be considered that the label information and the housing area of ​​the user's housing purchase demand are 80% similar.

[0045] Specifically, the matching degree can be expressed by a calculation formula: a1*quantity matching degree+a2*target similarity, wherein a1 and a2 are weight coefficients of the matching degree, and both a1 and a2 are positive numbers, and their sum is 1. Exemplarily, in an unknown scenario, the two weight coefficients are generally set to 1 / 2 a priori. The actual effect may be affected by the promotion of the house and the different user groups. The two weight coefficients can be adjusted according to the actual scenario. For example, in a scenario where the promotion of the house has a main and attractive selling point, a2 can be set larger for targeted sales promotion; in the scenario where the main promotion is for some unsold houses, a1 can be set larger to discover more potential buyers.

[0046] S230: In response to the joining request, send second information to the second client, where the second information includes the account and / or link of the target group.

[0047] Among them, after receiving the joining request, the first client can add the user account of the second client and send a second message to the second client in response to the joining request. The second message may include the account and / or link of the determined target group, so as to automatically recommend the group that publishes housing information to the user, thereby saving the property consultant's time in user management and operation.

[0048] In a possible example, the method also includes: after the second client joins the target group, labeling the second client with a label list according to the user's housing purchase needs, the label list including at least one label; according to the label list, filtering out a second data set from the first data set, the first data set including all housing information, the second data set including second housing information, the second housing information being housing information within the first range that meets the user's housing purchase needs; and sending the second data set to the second client.

[0049] In the embodiment of the present application, the first client can also carry out refined operations on users to achieve precision marketing. After the user using the second client joins the target group, in order to achieve precision marketing, the first client can add the users who have joined the group to the dynamic tag group, screen the users who participate in the activity, and prepare for subsequent precise reach. For example, a preferential activity of a villa real estate can be set through conditions, and the rules and links of the preferential activity can be sent to users who have joined the "high-end house" tag group.

[0050] Specifically, the first client can use the user's housing demand as a tag of the user of the second client, and then filter out all the housing information matching the tags in the tag list from the first data set including the housing information, and send the filtered housing information to the second client for the user to browse. The housing information in the second data set is valid housing information (i.e., housing that the user can currently rent or sell) or currently active housing information.

[0051] For example, the first client can also adjust its label list according to the house information browsed by the user in the second data set to achieve precision marketing. For example, if the houses viewed by the user are all second-hand houses with three bedrooms and two living rooms, the two bedrooms and one living room in the label list can be modified to three bedrooms and two living rooms.

[0052] For example, the first client can also send the house information and member-exclusive coupons of users who match the tag group from the first data set to the second client. Furthermore, the first client can also remove the tag group of the users who have been reached to avoid repeated sending, which saves time and convenience and reduces a lot of labor costs.

[0053] Optionally, the method also includes: receiving third information from the second client, the third information including third housing information, and the third housing information is the housing information browsed by the second client; comparing the third housing information with the user's housing purchase demand to obtain a comparison result; determining a second distance based on the comparison result, and modifying the label list based on the comparison result to obtain a modified label list, and the second distance is greater than the first distance; filtering out a third data set from the first data set according to the modified label list, the third data set including fourth housing information, and the fourth housing information is housing information between a second range and the first range, the second range is a circle center range with the third position as the center and the second distance as the radius, and the third position is the geographical location of the housing in the third housing information; sending the third data set to the second client.

[0054] In an embodiment of the present application, the first client may also modify its tag list and the user's housing purchase requirements based on the user's housing browsing history on the second client, while increasing the scope of housing screening.

[0055] The first client compares the house information of the browsing record fed back by the second client with the user's housing demand or tag list. If the third house information completely matches the user's housing demand or tag list, it means that the user's housing demand has not changed and does not need to be updated; if the third house information partially matches or completely does not match the user's housing demand or tag list, the unmatched options in the third house information are added to the user's demand list and tag list for modification and update.

[0056] Furthermore, when the comparison result is a mismatch or a partial match, the scope of the house search may be expanded. The difference between the second distance and the first distance may be pre-set or determined based on the user's browsing history, which is not limited in the present embodiment.

[0057] Specifically, when there are newly added tags in the house information browsed by the user, the first client can expand the search scope of the first data set and modify the user's house purchase requirements in real time according to the user's feedback to improve its work efficiency and customer success conversion rate. Specifically, the first client selects the house information that meets the updated user's house purchase requirements between the second range and the first range (i.e., within the expanded range), and sends it to the second client for the user to browse.

[0058] In a possible example, the method also includes: according to the label list, filtering out a fourth data set from the first data set, the fourth data set including fifth housing source information, the fifth housing source information being housing source information that has been successfully traded within the first range and meets the user's housing purchase needs; obtaining transaction information of each housing source information in the fourth data set, the transaction information being used to indicate a land price index, a transaction method, a remaining useful life and a floor area ratio; calculating a price correction coefficient for each housing source information in the second data set based on the housing source information in the second data set, the housing source information in the fourth data set, and the transaction information of each housing source information in the fourth data set; and correcting the price range of each housing source in the second data set based on the price correction coefficient to obtain a first corrected price range.

[0059] In practical applications, objective factors such as the transaction mode of real estate and the age of the house will also affect the evaluation price range of the house. Therefore, in the embodiment of the present application, after obtaining the price range of the house, the price range can also be corrected by objective factors according to the transaction information of the house.

[0060] Specifically, the transaction information of the houses in the multiple house transaction cases is obtained from the database, the transaction information of the recommended houses is obtained from the database or the relevant website, and according to the difference between the transaction information of the houses in the house transaction cases and the transaction information of the recommended houses, the mapping relationship between the difference and the objective correction coefficient is determined through a preset table, so as to determine the objective correction coefficient of the land to be evaluated. Then, the obtained price range is corrected according to the objective correction coefficient to obtain a first corrected price range.

[0061] Optionally, the method also includes: obtaining the distance between the first house source and multiple second houses source to obtain multiple distances to be corrected, wherein the first house source is a house source corresponding to any house source information in the second data set, and the second house source is a house source corresponding to house source information in the fourth data set that matches the house source information of the first house source; based on the multiple distances to be corrected, correcting the first corrected price range of the first house source to obtain a second corrected price range.

[0062] Among them, users are generally more concerned about the price range of the house. Considering that the distance between the house in the house transaction case and the recommended house may affect the accuracy of the price range of the recommended house, after calculating the first revised price range of the house, the weighted value of the distance between the house in the house transaction case with the same house information as the recommended house and the recommended house can be calculated. There is a mapping relationship between the weighted value of the distance and the price correction coefficient. According to the weighted value of the distance, the first revised price range can be corrected to obtain the final evaluation price range of the house.

[0063] It can be seen that the present application proposes a group recommendation method, wherein a first client receives a joining request from a second client, the joining request carries first information and a first position, the first position being the position of a graphic code scanned by the second client, and the first information being the house information of the advertisement where the graphic code is located; the target group of the second client is determined according to the first information and the first position; in response to the joining request, second information is sent to the second client, the second information including the account number and / or link of the target group. The present application can save the time of property consultants in user management and operation by being able to recommend suitable groups to users, thereby improving their work efficiency and customer success conversion rate.

[0064] The above mainly introduces the scheme of the embodiment of the present application from the perspective of the execution process on the method side. It is understandable that in order to realize the above functions, the network device includes a hardware structure and / or software module corresponding to each function. Those skilled in the art should easily realize that, in combination with the units and algorithm steps of each example described in the embodiment provided in this article, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0065] See also Figure 3 , Figure 3 is a functional unit composition block diagram of a group recommendation device 300 provided in an embodiment of the present application. The device 300 is applied to a terminal device. The device 300 includes: a transceiver unit 310 and a processing unit 320, wherein:

[0066] The transceiver unit 310 is configured to receive a joining request from a second client, the joining request carrying first information and a first position, the first position being the position of the graphic code scanned by the second client, the first information including first housing source information, and the first housing source information being the housing source information of the advertisement where the graphic code is located;

[0067] The processing unit 320 is configured to determine a target group of the second client according to the first information and the first location;

[0068] The transceiver unit 310 is further configured to send second information to the second client in response to the joining request, where the second information includes an account and / or link of the target group.

[0069] Optionally, the house source information includes a second location, where the second location is a geographical location of the house source;

[0070] In terms of determining the target group of the first client based on the first information and the first position, the processing unit 320 is specifically used to: calculate a first distance, where the first distance is the distance between the second position and the first position; screen out at least one candidate group from all groups of the first client, where the service range of the candidate group is larger than a first range, where the first range is a range centered on the first position or the second position and with the first distance as a radius; determine the user's housing purchase demand based on the first information; calculate the degree of match between each candidate group in the at least one candidate group and the user's housing purchase demand; and determine the candidate group corresponding to the maximum degree of match as the target group.

[0071] Optionally, the user's housing purchase requirements include at least one of the following: apartment type, apartment area, house type, and price range;

[0072] In terms of calculating the matching degree between each candidate group in the at least one candidate group and the user's housing demand, the processing unit 320 is specifically used to: obtain label information of the at least one candidate group to obtain at least one label information; determine the priority of the apartment type, the apartment area, the house type and the price range according to the characteristics of the housing source; calculate the quantity matching degree and target similarity of each label information in the at least one label information and the user's housing demand according to the priority level; calculate the matching degree of each candidate group according to the quantity matching degree and the target similarity.

[0073] Optionally, the processing unit 320 is further configured to: after the second client joins the target group, add a label list to the second client according to the user's housing purchase demand, the label list including at least one label; and filter out a second data set from the first data set according to the label list, the first data set including all housing source information, and the second data set including housing source information that meets the user's housing purchase demand within the first range;

[0074] The transceiver unit 310 is further configured to send the second data set to the second client.

[0075] Optionally, the transceiver unit 310 is further configured to: receive third information from the second client, the third information including third house source information, the third house source information being the house source information browsed by the second client;

[0076] The processing unit 320 is further configured to: compare the third housing source information with the user's housing purchase demand to obtain a comparison result; determine a second distance based on the comparison result, and modify the label list based on the comparison result to obtain a modified label list, wherein the second distance is greater than the first distance; filter out a third data set from the first data set according to the modified label list, wherein the third data set includes fourth housing source information, wherein the fourth housing source information is housing source information between a second range and the first range, wherein the second range is a range of a circle with the third position as the center and the second distance as the radius, and wherein the third position is a geographical location of a housing source in the third housing source information;

[0077] The processing unit 320 is further configured to send the third data set to the second client.

[0078] Optionally, the processing unit 320 is also used to: filter out a fourth data set from the first data set according to the label list, the fourth data set including fifth housing source information, the fifth housing source information being housing source information that has been successfully traded within the first range and meets the user's housing purchase needs; obtain transaction information of each housing source information in the fourth data set, the transaction information being used to indicate a land price index, a transaction method, a remaining useful life and a floor area ratio; calculate a price correction coefficient for each housing source information in the second data set based on the housing source information in the second data set, the housing source information in the fourth data set, and the transaction information of each housing source information in the fourth data set; and correct the price range of each housing source in the second data set based on the price correction coefficient to obtain a first corrected price range.

[0079] Optionally, the processing unit 320 is further used to: obtain the distance between the first house source and multiple second houses source to obtain multiple distances to be corrected, the first house source is a house source corresponding to any house source information in the second data set, and the second house source is a house source corresponding to the house source information in the fourth data set that matches the house source information of the first house source; based on the multiple distances to be corrected, correct the first corrected price range of the first house source to obtain a second corrected price range.

[0080] It should be understood that the device 300 here is embodied in the form of a functional unit. The term "unit" here may refer to an application specific integrated circuit (ASIC), an electronic circuit, a processor (such as a shared processor, a proprietary processor or a group processor, etc.) and a memory for executing one or more software or firmware programs, a merged logic circuit and / or other suitable components that support the described functions. In an optional example, those skilled in the art can understand that the device 300 can be specifically the vehicle-mounted device in the above-mentioned embodiment, and the device 300 can be used to execute the various processes and / or steps corresponding to the vehicle-mounted device in the above-mentioned method embodiment. To avoid repetition, it will not be repeated here.

[0081] The apparatus 300 of each of the above schemes has the function of implementing the corresponding steps executed by the vehicle-mounted device in the above method; the function can be implemented by hardware, or by hardware executing the corresponding software. The hardware or software includes one or more modules corresponding to the above functions; for example, the transceiver unit 310 can be replaced by a transmitter, and the processing unit 320 can be replaced by a processor, respectively performing the transceiver operations and related processing operations in each method embodiment.

[0082] In the embodiment of the present application, the device 300 may also be a chip or a chip system, such as a system on chip (SoC). Correspondingly, the transceiver unit may be a transceiver circuit of the chip, which is not limited here.

[0083] See also Figure 4 , Figure 4 It is a structural diagram of a terminal device provided in an embodiment of the present application, wherein the terminal device comprises: one or more processors, one or more memories, one or more communication interfaces, and one or more programs; the one or more programs are stored in the memories and are configured to be executed by the one or more processors.

[0084] The above-mentioned program includes instructions for executing the following steps: receiving a joining request from a second client, the joining request carrying first information and a first position, the first position being the position of a graphic code scanned by the second client, the first information including first housing information, the first housing information being the housing information of the advertisement where the graphic code is located; determining a target group of the second client based on the first information and the first position; and sending second information to the second client in response to the joining request, the second information including an account and / or link of the target group.

[0085] Among them, all relevant contents of each scenario involved in the above method embodiment can be referred to the functional description of the corresponding functional module, which will not be repeated here.

[0086] It should be understood that the above-mentioned memory may include a read-only memory and a random access memory, and provide instructions and data to the processor. A portion of the memory may also include a non-volatile random access memory. For example, the memory may also store information about the device type.

[0087] In the embodiment of the present application, the processor of the above-mentioned device may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0088] It should be understood that the "at least one" involved in the embodiments of the present application refers to one or more, and "plurality" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent: the existence of A alone, the existence of A and B at the same time, and the existence of B alone, where A and B can be singular or plural. The character " / " generally indicates that the previous and subsequent associated objects are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple.

[0089] Furthermore, unless otherwise specified, the ordinal numbers such as "first" and "second" mentioned in the embodiments of the present application are used to distinguish multiple objects, and are not used to limit the order, timing, priority or importance of multiple objects. For example, the first information and the second information are only used to distinguish different information, and do not indicate the difference in content, priority, sending order or importance of the two types of information.

[0090] In the implementation process, each step of the above method can be completed by an integrated logic circuit of hardware in a processor or an instruction in the form of software. The steps of the method disclosed in conjunction with the embodiment of the present application can be directly embodied as a hardware processor for execution, or a combination of hardware and software units in a processor for execution. The software unit can be located in a storage medium mature in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium is located in a memory, and the processor executes the instructions in the memory, and completes the steps of the above method in conjunction with its hardware. To avoid repetition, it is not described in detail here.

[0091] An embodiment of the present application also provides a computer storage medium, wherein the computer storage medium stores a computer program for electronic data exchange, and the computer program enables a computer to execute part or all of the steps of any method recorded in the above method embodiments.

[0092] The present application also provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute some or all of the steps of any method described in the above method embodiment. The computer program product may be a software installation package.

[0093] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present application.

[0094] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0095] In the several embodiments provided in the present application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the above-mentioned units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0096] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiments of the present application.

[0097] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0098] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or all or part of the technical solution, can be embodied in the form of a software product, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, server or TRP, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk and other media that can store program codes.

[0099] A person skilled in the art may understand that all or part of the steps in the various methods of the above embodiments may be completed by instructing the relevant hardware through a program, and the program may be stored in a computer-readable memory, which may include a flash drive, ROM, RAM, a magnetic disk or an optical disk, etc.

[0100] The embodiments of the present application are introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method and core idea of ​​the present application. At the same time, for general technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A group recommendation method, characterized in that: Applied to a first client, the method includes: receiving a joining request from a second client, the joining request carrying first information and a first location, the first location being the location of the graphic code scanned by the second client, the first information including first housing source information, the first housing source information being the housing source information of the advertisement where the graphic code is located, the first housing source information including a second location, and the second location being the geographical location of the housing source; Determining a target group of the second client according to the first information and the first position includes: calculating a first distance, where the first distance is the distance between the second position and the first position; screening out at least one candidate group from all groups of the first client, where the service range of the candidate group is larger than the first range, where the first range is a range centered on the first position or the second position and having the first distance as a radius; determining a user's housing purchase demand according to the first information, where the user's housing purchase demand includes apartment type, apartment area, house type and price range; acquiring label information of the at least one candidate group to obtain at least one label information; determining the apartment type, apartment area, house type and price range according to the characteristics of the house source; and the priority of the price range; according to the priority, respectively calculate the quantity matching degree and target similarity of each tag information in the at least one tag information and the user's housing purchase demand, the quantity matching degree is used to characterize the number of information matching the tag information in the apartment type, the apartment area, the house type and the price range included in the user's housing purchase demand, and the target similarity is used to characterize the similarity between the tag information and each information in the apartment type, the apartment area, the house type and the price range included in the user's housing purchase demand; calculate the matching degree of each candidate group with the user's housing purchase demand according to the quantity matching degree and the target similarity; determine the candidate group corresponding to the maximum matching degree as the target group; In response to the joining request, second information is sent to the second client, where the second information includes an account and / or a link of the target group.

2. The method according to claim 1, characterized in that The method further comprises: After the second client joins the target group, a tag list is added to the second client according to the user's housing purchase demand, wherein the tag list includes at least one tag; According to the tag list, a second data set is filtered out from the first data set, wherein the first data set includes all housing source information, and the second data set includes second housing source information, and the second housing source information is housing source information that meets the housing purchase demand of the user within the first range; The second data set is sent to the second client.

3. The method according to claim 2, characterized in that The method further comprises: Receiving third information from the second client, the third information including third house source information, the third house source information being the house source information browsed by the second client; Compare the third housing source information with the user's housing purchase demand to obtain a comparison result; determining a second distance based on the comparison result, and modifying the tag list based on the comparison result to obtain a modified tag list, wherein the second distance is greater than the first distance; A third data set is filtered out from the first data set according to the modification tag list, the third data set includes fourth house source information, the fourth house source information is house source information between a second range and the first range, the second range is a circle center range with the third position as the center and the second distance as the radius, and the third position is the geographical location of the house in the third house source information; The third data set is sent to the second client.

4. The method according to claim 2, characterized in that: The method further comprises: According to the tag list, a fourth data set is screened out from the first data set, wherein the fourth data set includes fifth housing source information, and the fifth housing source information is housing source information that has been successfully traded within the first range and meets the housing purchase demand of the user; Acquire transaction information of each house source information in the fourth data set, wherein the transaction information is used to indicate a land price index, a transaction method, a remaining useful life, and a floor area ratio; Calculate a price correction coefficient for each piece of housing information in the second data set based on the housing information in the second data set, the housing information in the fourth data set, and the transaction information of each piece of housing information in the fourth data set; The price range of each house in the second data set is corrected based on the price correction coefficient to obtain a first corrected price range.

5. The method according to claim 4, characterized in that The method further comprises: The distance between a first house source and multiple second houses sources is obtained to obtain multiple distances to be corrected, wherein the first house source is a house source corresponding to any house source information in the second data set, and the second house source is a house source corresponding to house source information in the fourth data set that matches the house source information of the first house source; based on the multiple distances to be corrected, a first corrected price range of the first house source is corrected to obtain a second corrected price range.

6. A group recommendation device, characterized in that: Applied to a first client, the device comprises: a transceiver unit, configured to receive a joining request from a second client, the joining request carrying first information and a first location, the first location being the location of the graphic code scanned by the second client, the first information comprising first housing source information, the first housing source information being the housing source information of the advertisement where the graphic code is located, the first housing source information comprising a second location, and the second location being the geographical location of the housing source; A processing unit is used to determine a target group of the second client according to the first information and the first position, including: calculating a first distance, where the first distance is the distance between the second position and the first position; screening out at least one candidate group from all groups of the first client, where the service range of the candidate group is larger than a first range, where the first range is a range with the first position or the second position as the center and the first distance as the radius; determining a user's housing purchase demand according to the first information, where the user's housing purchase demand includes apartment type, apartment area, house type and price range; acquiring label information of the at least one candidate group to obtain at least one label information; determining the apartment type, apartment area, house type and price range according to the characteristics of the house source; the priority of the house type and the price range; according to the priority, respectively calculate the quantity matching degree and target similarity of each tag information in the at least one tag information and the user's housing purchase demand, the quantity matching degree is used to characterize the number of information matching the tag information in the house type, the house type area, the house type and the price range included in the user's housing purchase demand, and the target similarity is used to characterize the similarity between the tag information and each information in the house type, the house type area, the house type and the price range included in the user's housing purchase demand; calculate the matching degree of each candidate group with the user's housing purchase demand according to the quantity matching degree and the target similarity; determine the candidate group corresponding to the maximum matching degree as the target group; The transceiver unit is further configured to send second information to the second client in response to the joining request, where the second information includes an account number and / or a link of the target group.

7. A terminal device, characterized in that: The terminal device includes a processor, a memory and a communication interface, the memory stores one or more programs, and the one or more programs are executed by the processor, and the one or more programs include instructions for executing the steps in the method as described in any one of claims 1-5.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program for electronic data exchange, wherein the computer program enables a computer to execute the steps of the method according to any one of claims 1 to 5.

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