CN113779379A

CN113779379A - User portrait based house source pushing method, device and equipment and storage medium

Info

Publication number: CN113779379A
Application number: CN202110921893.3A
Authority: CN
Inventors: 翁浩敬
Original assignee: Shenzhen Ideamake Software Technology Co Ltd
Current assignee: Shenzhen Ideamake Software Technology Co Ltd
Priority date: 2021-08-11
Filing date: 2021-08-11
Publication date: 2021-12-10

Abstract

The embodiment of the application discloses a user portrait-based house source pushing method, device, equipment and storage medium, wherein the method comprises the following steps: acquiring user information of a target user, and determining a user type of the target user according to the user information; determining at least one house source label required by a target user according to the user type; determining first house source information in a plurality of geographic areas, wherein the first house source information comprises house source information of at least one house; determining a recommendation score of each house in the first house source information according to the geographic position of each house in the first house source information, at least one house source label and a recommendation weight value corresponding to each geographic area; the house source information corresponding to each house in the first house source information is sorted according to the recommended scores, and the sorted first house source information is sent to the terminal of the target user, so that the matching degree of house sources pushed to the target user can be improved, and the efficiency of searching for proper house sources by the target user is improved.

Description

User portrait based house source pushing method, device and equipment and storage medium

Technical Field

The application relates to the technical field of computers, in particular to a house source pushing method based on user portrait and a related product thereof.

Background

With the development of economy, the demand of people for houses is increasing day by day. At present, the house resources are pushed to users, through subjective impressions and investigation results of developers, some cities are manually configured into an urban circle in a PC management background, and the house resources are displayed in the urban circle; or the house resources in a certain range around are divided into house resources in the urban circle through the geographic position authorized by the user and are displayed to the user. Because everyone is inconsistent to the demand in different types of houses, the above-mentioned mode of propelling movement house resources to the user can not satisfy user's actual demand, and the house resources matching degree of propelling movement is low, and the user still need spend more time to find suitable house resources.

Disclosure of Invention

The embodiment of the application mainly aims to provide a house source pushing method based on a user portrait and a related product thereof, which can improve the accuracy of pushing a house source to a user.

In a first aspect, an embodiment of the present application provides a method for pushing a house source based on a user portrait, where the method includes:

acquiring user information of a target user, and determining a user type of the target user according to the user information, wherein the user type is used for indicating the identity characteristics of the target user;

determining at least one house source label required by the target user according to the user type;

determining first house source information in a plurality of geographic areas, wherein the first house source information comprises house source information of at least one house;

determining a recommended score of each house in the first house source information according to the geographic position of each house in the first house source information, the at least one house source label and the recommended weight value corresponding to each geographic area;

and sorting the house source information corresponding to each house in the first house source information according to the recommended scores, and sending the sorted first house source information to the terminal of the target user.

In a second aspect, an embodiment of the present application provides a user portrait-based house source pushing device, where the device includes:

the device comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring user information of a target user and determining a user type of the target user according to the user information, and the user type is used for indicating the identity characteristics of the target user;

the first determining unit is used for determining at least one house source label required by the target user according to the user type;

the second determining unit is used for determining first house source information in a plurality of geographic areas, and the first house source information comprises house source information of at least one house;

a third determining unit, configured to determine a recommended score of each house in the first house information according to a geographic location of each house in the first house information, the at least one house label, and a recommended weight value corresponding to each geographic area;

and the sending unit is used for sequencing the house source information corresponding to each house in the first house source information according to the recommendation scores and sending the sequenced first house source information to the terminal of the target user.

In a third aspect, an embodiment of the present application provides an electronic device, including a processor, a memory, a communication interface, and one or more programs, where 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 steps in any method of the first aspect of the embodiment of the present application.

In a fourth aspect, the present application provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program for electronic data exchange, where the computer program makes a computer perform part or all of the steps described in any one of the methods of the first aspect of the present application.

In a fifth aspect, 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 perform some or all of the steps as described in any one of the methods of the first aspect of the embodiments of the present application. The computer program product may be a software installation package.

It can be seen that, in the embodiment of the application, the user type of the target user is determined according to the user information by acquiring the user information of the target user; determining at least one house source label required by the target user according to the user type; determining first house source information in a plurality of geographic areas, wherein the first house source information comprises house source information of at least one house; determining a recommended score of each house in the first house source information according to the geographic position of each house in the first house source information, the at least one house source label and the recommended weight value corresponding to each geographic area; and sorting the house source information corresponding to each house in the first house source information according to the recommended scores, and sending the sorted first house source information to the terminal of the target user, so that the matching degree of house sources pushed to the target user can be improved, and the efficiency of searching for proper house sources by the target user is improved.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.

Fig. 1 is a schematic view of an application scenario of house source push provided in an embodiment of the present application;

fig. 2A is a schematic flowchart of a method for pushing a house source based on a user portrait according to an embodiment of the present disclosure;

fig. 2B is a schematic structural diagram of house source information and house source tags according to an embodiment of the present application;

fig. 3 is a schematic flowchart of a method for pushing a house source based on a user portrait according to an embodiment of the present disclosure;

fig. 4 is a schematic structural diagram of an electronic device provided in an embodiment of the present application;

fig. 5 is a block diagram illustrating functional units of a user portrait-based house source pushing apparatus according to an embodiment of the present application.

Detailed Description

In order to make the technical solutions of the present application better understood, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

The terms "first," "second," and the like in the description and claims of the present application and in the above-described drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.

In order to realize the effect of recommending the house resources in the first city circle of the system, the current technical scheme mainly adopts two modes:

1. according to subjective impressions and research results of developers, some cities are manually configured into an urban circle in a PC management background, and house sources in the cities are displayed in the urban circle;

2. and according to the geographic position authorized by the C-end user, dividing the house resources in a certain range around the house into urban circles and displaying the urban circles to the client.

There are some drawbacks and drawbacks to the existing methods. The above method 1 cannot dynamically update the house source information in the urban area, cannot achieve the effect of personal recommendation, and cannot better recommend house sources for customers who want to invest or have better economic strength. And the mode 2 is not strict enough as the recommendation condition purely according to the geographical location information authorized by the user, which can cause wrong recommendation. For example, a white collar on work in southern sand, Guangzhou wanted to purchase houses in cities with lower surrounding housing prices, and the house source of Dongguan or Zhongshan should be added to the city circle and recommended to the user. However, the house source of the Shenzhen Baoan region may be added into the urban circle and recommended at a position far ahead in the urban circle by only recommending according to the authorized geographic position of the user, and the house prices of the two regions are not greatly different from each other for the user, so that the appeal of the user cannot be realized.

The following describes embodiments of the present application in detail.

Referring to fig. 1, fig. 1 is a schematic diagram of a user portrait based house source pushing system according to an embodiment of the present application, where the user portrait based house source pushing system includes an electronic device 101, and a user can find house source information with high matching degree through the electronic device 101.

In order to better adapt to different user groups, the system takes the house source information in a first-line city and a new first-line city as the type A house source information, takes the house source information of a common city as the type B house source information or takes the house source information of a city to which the geographic position provided by a target user belongs as the type B house source information, and divides each house source information structure into two types of AB to adapt to different user groups.

And finally, the configuration of the urban circle adapted to the target user can be completed only by setting a distance threshold value as the urban circle range by a manager in a system management background.

When a client target user enters the system, after authorization, the method firstly judges whether the current target user has a user portrait in the system, and can carry out classification recommendation on the house source information of the urban area in a targeted manner for the target user who has the user portrait.

If the target user has a user portrait, the system grades the target user according to the information of the target user such as age, occupation, income and the like, and judges whether the target user is an investment type client or an on-demand type client.

If the target user is an investment type client, the house source selection of the urban area determines the A-type house source information from near to far in the distance threshold range set by the PC management background according to the current authorized geographic position of the user, searches the A-type house source information for the house source information with the comprehensive score meeting the first preset condition in the 'commercial', 'education' and 'medical' module in each house source information, and adds the house source information into the house source information of the urban area. The system can also retrieve the B-type house source information, but can perform right reduction processing on the comprehensive scores in the business, education and medical modules in each house source information in the B-type house source information, and the ranking is placed behind the A-type house source information. Then once the user has retrieved a city in the metro ring in the system, the system places the house ordering for that city at the top inside the metro ring.

And if the target user is a client needing the type just, retrieving the house source information of which the comprehensive scores in the traffic, house type and price modules in each house source information in the B type house source information meet a second preset condition. And the system only searches the house source information of the A-type city where the current user is positioned, and performs right reduction processing on the search result to sort the house sources at the end. This avoids the customer who cannot afford Guangzhou's rate from seeing a large amount of Shenzhen's origins in the metro circle.

If the user does not have the user portrait, the system firstly uses the authorized position to belong to the A-type house source information or the B-type house source information, if the positioning position belongs to the A-type city, the system firstly defaults to divide the urban circle according to the classification mode of the 'just needed' user in consideration of the house purchasing pressure of the A-type city, and after the user searches the house source of a certain city, the city also can be added into the urban circle. If the user just needing to belong to the B-type city, the system can directly divide the urban circle according to the set distance threshold, but after the user searches a certain city, the city also can be added into the urban circle.

In order to solve the problem of low matching degree of the house source pushed to the user, the application provides a house source pushing method based on a user portrait, and as shown in fig. 2A specifically, the method may include, but is not limited to, the following steps:

s201, the electronic equipment acquires user information of a target user and determines a user type of the target user according to the user information;

the electronic device according to the embodiment of the present application may be an electronic device with a communication capability, the electronic device may be a server, and the electronic device may include various handheld devices with a wireless communication function, vehicle-mounted devices, wearable devices, computing devices or other processing devices connected to a wireless modem, and various forms of User Equipment (UE), a Mobile Station (MS), a terminal device (terminal device), and the like.

The user information includes identity information, age information, occupation information, income information, and asset information of the target user, and the user information further includes other personal information of the target user, such as deposit information, consumption information, and the like, where the user information is not limited too much.

Wherein the user type is used for indicating the identity of the target user.

In one possible example, the user type includes the on-demand type and the investment type, or other predetermined categories, without limitation.

Specifically, the electronic device in step S201 acquires the user information of the target user, and determines the user type of the target user according to the user information, including the following specific steps:

step A1: the electronic equipment acquires user information uploaded by a target user, or acquires a user image or fingerprint information or iris information or voiceprint information or password information of the target user, determines user identity information of the target user according to the user image or fingerprint information or iris information or voiceprint information or password information of the target user, and determines user information according to the user identity information;

among them, to be further explained are: the step a1 of acquiring, by the electronic device, the user information uploaded by the target user may be: the electronic equipment acquires characters which are directly uploaded by a target user and are related to user information, or the electronic equipment acquires an image which is directly uploaded by the target user and is related to the user information, and identifies character parts in the image to obtain the user information.

Among them, to be further explained are: in the step a1, the electronic device obtains the face image or the fingerprint information or the iris information or the voiceprint information or the password information of the target user, determines the user identity information of the target user according to the face image or the fingerprint information or the iris information or the voiceprint information or the password information of the target user, and determines the user information according to the user identity information, where the determining may be:

the electronic equipment acquires a face image of a target user, further selects a face area according to the face image, compares the face area with a face image in a preset face image set, identifies identity information of the target user, and determines user information of the target user according to the identity information of the target user.

the electronic equipment acquires the fingerprint information of a target user, compares the fingerprint information with fingerprint information in a preset fingerprint information set one by one, determines the identity information of the target user, and determines the user information of the target user according to the identity information of the target user.

the electronic equipment acquires a user image of a target user, intercepts an iris area in the user image, determines iris information of the target user according to the iris area, determines identity information of the target user according to the iris information, and determines user information of the target user according to the identity information of the target user.

the electronic equipment acquires a section of voice of a target user, determines voiceprint information of the target user according to the voice, determines identity information of the target user according to the voiceprint information, and determines user information according to the identity information of the target user.

the electronic equipment acquires password information uploaded by a target user, determines identity information of the target user according to the password information, and determines user information of the target user according to the identity information of the target user.

Step A2: the electronic equipment determines scores corresponding to various user information indexes in the user information;

further, in step a2, the electronic device determines the score corresponding to each user information index in the user information, including the following specific steps:

and the electronic equipment determines the scores corresponding to all the user information indexes in the user information according to the mapping relation between the user information indexes and the user information scores.

Step A3: and the electronic equipment analyzes the user type corresponding to the target user according to the scores corresponding to the various user information indexes.

Further, in step a3, the electronic device analyzes the user type corresponding to the target user according to the score corresponding to each user information index, and includes the following specific steps:

the electronic equipment calculates the corresponding user type score of the target user according to the scores corresponding to the various user information indexes, and determines the user type corresponding to the score interval, namely the user type corresponding to the target user according to the score interval to which the user type score belongs.

In a possible example, the determining, in step S201, the user type of the target user according to the user information includes the following specific steps:

step B1: the electronic equipment determines the user type score of a target user according to personal information, work information, income information and asset information of the user in the user information;

specifically, the electronic device determines the user type score of the target user according to the personal information, the work information, the income information, and the asset information of the user in the user information, and may include the following specific steps: the electronic equipment determines a score corresponding to the personal information, a score corresponding to the work information, a score corresponding to the income information and a score corresponding to the asset information, and calculates a user type score of the target user according to a user type calculation formula, the score corresponding to the personal information, the score corresponding to the work information, the score corresponding to the income information and the asset information.

The user type calculation formula may be:

w is the score of user type, i is the number one in user informationSeveral items of information, for example, personal information may be a first item of information, work information may be a second item of information, income information may be a third item of information, property information may be a fourth item of information, α_iIs corresponding to item i; a. the_iThe score corresponding to the ith item of information.

Step B2: and the electronic equipment determines the user type of the target user according to the user type score.

Specifically, the electronic device determines the user type of the target user according to the user type score in step B2, which includes the following specific steps:

and the electronic equipment determines the user type of the target user according to the preset user type score, the mapping relation of the user types and the user type score.

S202, the electronic equipment determines at least one house source label required by a target user according to the user type;

the house source label can be traffic, education, business, house type, price and medical treatment, and can also be a city where the house source is located and other preset labels, so that limitation is not performed.

If the target user is an investment type, the house source label required by the target user can comprise any one of traffic, education and business, and the house source label required by the target user can also comprise other types of house source labels, which is not limited herein; if the target user is of the on-demand type, the house source tags required by the target user may include: any house source label of house type, price and medical treatment, and the house source label required by the target user can also comprise other types of house source labels, which is not limited herein.

S203, the electronic equipment determines first house source information in a plurality of geographic areas;

wherein the first house source information comprises house source information of at least one house. Each house source in the first house source information comprises at least one house source label and a numerical value corresponding to each house source label, as shown in fig. 2B, each house source determines a numerical value corresponding to transportation, education, business and medical treatment in the house source label according to the geographical position of the house source, for example, the house source C determines the distance or the time spent from the geographical position of the house source to transportation stations such as train stations, bus stations, subway stations and bus stations, and determines a numerical value corresponding to the transportation of the house source label according to the distance and the time spent; c, determining a numerical value corresponding to the house source label education according to the distance from the geographical position of the house source to schools such as key primary schools in the province, key primary schools in the city, key kindergarten and the like or the spent time of the house source; and C, determining a numerical value corresponding to the house source label business according to the distance from the geographical position of the house source to the business positions of nearby superstores, commercial streets, urban collections and the like or the time spent by the house source.

The plurality of geographic areas comprise a first geographic area type A city and a second geographic area type B city, and the first geographic area type A city is different from the second geographic area type B city; the first house source information includes: second house source information A type house source information and third house source information B type house source information, wherein the second house source information A type house source information is house source information corresponding to a first geographic region A type city, and the third house source information B type house source information is house source information corresponding to a second geographic region B type city. The first house source information may be of the same company

The city class a may include any one of first-line cities and supermini first-line cities, such as the cities of beijing, shanghai, guangzhou, shenzhen, hangzhou, chengdu, Chongqing, etc., and the city class B may include any one of second-line cities and third-line cities, may further include a city to which a location currently authorized by a target user belongs, and may further include a city historically searched by the target user.

S204, the electronic equipment determines a recommendation score of each house in the first house source information according to the geographic position of each house in the first house source information, at least one house source label and a recommendation weight value corresponding to each geographic area;

in a possible embodiment, the step S204 of determining, by the electronic device, the recommendation score of each house in the first house information according to the first geographic location of each house in the first house information, the at least one house label, and the recommendation weight value corresponding to each geographic area includes the following specific steps:

step C1: when the user type of the target user is the investment type, determining that a recommendation weight value corresponding to a first geographic area is a first recommendation weight value and a recommendation weight value corresponding to a second geographic area is a second recommendation weight value according to the investment type, wherein the first recommendation weight value is larger than the second recommendation weight value;

for example, when the target user is of the investment type, the first geographic region is determined to be a type a city according to the investment type, and the type a city may include any one of a first-line city and a super first-line city, such as cities of beijing, shanghai, guangzhen, shengzhou, Chengdu, Chongqing, and the like.

For example, when the target user is of the investment type, the second geographic area is determined to be a class B city according to the investment type, the class B city may include any one of a second-line city and a third-line city, such as a city of mansion, fuzhou, tin-free, fertile, kunming, harbourn, jianzhu, nanning, and the like, and may further include a city to which the current authorized location of the target user belongs, and may further include a city to which the target user has historically searched.

The first recommended weight value may be a preset weight value; may be a weight value determined according to the user information; the first geographical area may be a geographical area corresponding to the user type. For example, the first recommended weight value may be a numerical value of 1, 2, 3, 4, 5, 6, 4.5, 6.9, 10, 20, 30, 55, etc., which is only an example, and the numerical value of the first recommended weight value is not limited too much.

The second recommended weight value may be a preset weight value; may be a weight value determined according to the user information; the second geographical area may be a geographical area corresponding to the user type. For example, the second recommended weight value may be a numerical value such as 1, 2, 3, 4, 5, 6, 4.5, 6.9, 10, 20, 30, etc., which is only an example, and the numerical value of the second recommended weight value is not limited too much.

For example, the following specific steps may be taken to determine that the recommendation weight value corresponding to the first geographic area is the first recommendation weight value and the recommendation weight value corresponding to the second geographic area is the second recommendation weight value: and the target user determines that the recommendation weight value corresponding to the class A city is a first recommendation weight value 5, and the target user determines that the recommendation weight value corresponding to the class B city is a second recommendation weight value 1.

Step C2: determining a first recommendation score of each house in the second house source information according to the geographic position of each house in the second house source information, at least one house source label and the first recommendation weight value;

further, in step C2, the electronic device determines the first recommendation score of each house in the second room source information according to the geographic location of each house in the second room source information, the at least one room source label, and the first recommendation weight value, and the method includes the following specific steps:

step C21: the electronic equipment determines a label score corresponding to each house source label of at least one house source label according to the geographic position of each house in the second house source information;

step C22: and the electronic equipment performs weighted calculation to obtain a first recommendation score of each house in the second house source information according to the label score corresponding to each house source label and the first recommendation weight value.

The calculation formula for obtaining the first recommendation score of each house in the second house source information through weighting calculation may be:

wherein Q is a first recommendation score of each house in each house source information, mu is a first recommendation weight value corresponding to a class A city, n is the total number of house source labels, i is the serial number of the house source labels, and beta_iFor the label score corresponding to the ith room source label, b_iAnd the weight value is the weight value corresponding to the ith house source label. In the normal case b_i＝1，b_iOther preset values are possible, such as 2, 3, 4, 4.5, 5, 6, etcHere for b_iWithout undue limitation.

The calculation formula for obtaining the first recommendation score of each house in the second house information through weighted calculation may also be another calculation formula, which is not limited herein.

Step C3: the electronic equipment determines a second recommendation score of each house in the third house source information according to the geographic position of each house in the third house source information, at least one house source label and the second recommendation weight value;

further, in step C3, the electronic device determines a second recommendation score of each house in the third house information according to the geographic location of each house in the third house information, the at least one house label, and the second recommendation weight value, including the following specific steps:

step C31: the electronic equipment determines a label score corresponding to each house source label of at least one house source label according to the geographic position of each house in the third house source information;

step C32: and the electronic equipment performs weighted calculation according to the label score corresponding to each house source label and the second recommendation weight value to obtain the second recommendation score of each house in the third house source information.

The calculation formula for obtaining the second recommendation score of each house in the third house source information through weighting calculation may be:

wherein, P is the first recommendation score of each house in each house source information, ν is the second recommendation weight value corresponding to the B-type city, m is the total number of house source labels, i is the serial number of the house source labels, and χ_iA label score corresponding to the ith room source label, c_iAnd the weight value is the weight value corresponding to the ith house source label. In the usual case c_i＝1，c_iMay be other preset values, such as 2, 3, 4, 4.5, 5, 6, etc., where c is the same_iWithout undue limitation.

The calculation formula for obtaining the second recommendation score of each house in the third house source information through weighted calculation may also be another calculation formula, which is not limited herein.

Step C4: and determining the recommendation score of each house in the first house source information according to the first recommendation score and the second recommendation score.

In a possible embodiment, the step S204 of determining, by the electronic device, the recommendation score of each house in the first house information according to the geographic position of each house in the first house information, the at least one house label, and the recommendation weight value corresponding to each geographic area includes the following specific steps:

step D1: when the user type of the target user is a just-needed type, determining that a recommendation weight value corresponding to a first geographic area is a first recommendation weight value and a recommendation weight value corresponding to a second geographic area is a second recommendation weight value according to the just-needed type, wherein the first recommendation weight value is smaller than the second recommendation weight value;

step D2: determining a first recommendation score of each house in the second house source information according to the geographic position of each house in the second house source information, at least one house source label and the first recommendation weight value;

further, in step D4, the electronic device determines the first recommendation score of each house in the second room source information according to the geographic location of each house in the second room source information, the at least one room source label, and the first recommendation weight value, and the method includes the following specific steps:

step D21: the electronic equipment determines a label score corresponding to each house source label of at least one house source label according to the geographic position of each house in the second house source information;

step D22: and the electronic equipment performs weighted calculation to obtain a first recommendation score of each house in the second house source information according to the label score corresponding to each house source label and the first recommendation weight value.

wherein Q is a first recommendation score of each house in each house source information, mu is a first recommendation weight value corresponding to a class A city, n is the total number of house source labels, i is the serial number of the house source labels, and beta_iFor the label score corresponding to the ith room source label, b_iAnd the weight value is the weight value corresponding to the ith house source label. In the normal case b_i＝1，b_iMay be other preset values, e.g. 2, 3, 4, 4.5, 5, 6, etc., where for b_iWithout undue limitation.

Step D3: determining a second recommendation score of each house in the third house source information according to the geographic position of each house in the third house source information, at least one house source label and the second recommendation weight value;

further, in step D3, determining a second recommendation score of each house in the third house information according to the geographic location of each house in the third house information, the at least one house label, and the second recommendation weight value, includes the following specific steps:

step D31: the electronic equipment determines a label score corresponding to each house source label of at least one house source label according to the geographic position of each house in the third house source information;

step D32: and the electronic equipment performs weighted calculation according to the label score corresponding to each house source label and the second recommendation weight value to obtain the second recommendation score of each house in the third house source information.

wherein P is each house source letterThe first recommendation score of each house in the family, v is the second recommendation weight value corresponding to the B-type city, m is the total number of the house source labels, i is the serial number of the house source labels, and χ_iA label score corresponding to the ith room source label, c_iAnd the weight value is the weight value corresponding to the ith house source label. In the usual case c_i＝1，c_iMay be other preset values, such as 2, 3, 4, 4.5, 5, 6, etc., where c is the same_iWithout undue limitation.

Step D4: and determining the recommendation score of each house in the first house source information according to the first recommendation score and the second recommendation score.

S205, the electronic equipment sorts the house source information corresponding to each house in the first house source information according to the recommended scores, and sends the sorted first house source information to the terminal of the target user.

Specifically, the method further includes: if the target user does not have the user portrait, obtaining the authorized position of the target user, classifying the authorized position into a type A city or a type B city, if the authorized position belongs to the type A city, considering the house purchasing pressure of the type A city, the electronic equipment firstly defaults to classify the city circle corresponding to the house source recommended to the target user according to the classification mode of the user just needed, and when the target user searches the house source of a certain city, the city also can be added into the city circle. If the authorized position of the target user belongs to the class B city, the system can directly divide the urban circle according to the set distance threshold, but after the target user searches a certain city, the city also can be added into the urban circle. And the room source information with high adaptability is conveniently pushed to the target user.

It can be seen that the user type of the target user is determined according to the user information in the embodiment of the application; determining at least one house source label required by a target user according to the user type; determining first house source information in a plurality of geographic areas; determining a recommendation score of each house in the first house source information according to the geographical position of each house in the first house source information, at least one house source label and a recommendation weight value corresponding to each geographical area; the house source information corresponding to each house in the first house source information is sorted according to the recommended scores, and the sorted first house source information is sent to the terminal of the target user, so that the matching degree of house sources pushed to the target user can be improved, and the efficiency of searching for proper house sources by the target user is improved.

The embodiments of the present application will be described in detail below with reference to a specific example.

Referring to fig. 3, fig. 3 is a schematic flow chart illustrating a method for pushing a house source based on a user portrait according to an embodiment of the present application, consistent with the embodiment shown in fig. 2A, the method includes:

s301, the electronic equipment acquires user information of a target user;

s302, the electronic equipment determines the user type score of a target user according to personal information, work information, income information and asset information of the user in the user information;

s303, the electronic equipment determines the user type of the target user according to the user type score;

wherein the user type is used for indicating the identity of the target user.

S304, the electronic equipment determines at least one house source label required by a target user according to the user type;

s305, the electronic equipment determines first house source information in a plurality of geographic areas;

wherein the first house source information comprises house source information of at least one house.

S306, the electronic equipment determines the recommendation score of each house in the first house source information according to the geographic position of each house in the first house source information, at least one house source label and the recommendation weight value corresponding to each geographic area.

S307, the electronic equipment sorts the house source information corresponding to each house in the first house source information according to the recommended scores, and sends the sorted first house source information to the terminal of the target user.

It can be seen that, in the embodiment of the application, the user type score of the target user is determined according to the personal information, the work information, the income information and the asset information of the user in the user information by acquiring the user information of the target user; determining the user type of the target user according to the user type score; determining at least one house source label required by a target user according to the user type; determining first house source information in a plurality of geographic areas, wherein the first house source information comprises house source information of at least one house; determining a recommendation score of each house in the first house source information according to the geographic position of each house in the first house source information, at least one house source label and a recommendation weight value corresponding to each geographic area; the house source information corresponding to each house in the first house source information is sorted according to the recommended scores, and the sorted first house source information is sent to the terminal of the target user, so that the matching degree of house sources pushed to the target user can be improved, and the efficiency of searching for proper house sources by the target user is improved.

Referring to fig. 4, fig. 4 is a schematic structural diagram of an electronic device 400 according to an embodiment of the present disclosure, and as shown in the drawing, the electronic device 400 includes an application processor 410, a memory 420, a communication interface 430, and one or more programs 421, where the one or more programs 421 are stored in the memory 420 and configured to be executed by the application processor 410, and the one or more programs 421 include instructions for performing the following steps:

In one possible example, the determining the user type of the target user according to the user information includes: determining the user type score of the target user according to the personal information, the work information, the income information and the asset information of the user in the user information; and determining the user type of the target user according to the user type score.

In one possible example, the user types include: investment type and or on demand type.

In one possible example, the plurality of geographic regions includes a first geographic region and the second geographic region, the first geographic region being different from the second geographic region; the first house source information includes: second house source information and third house source information, wherein the second house source information is house source information corresponding to the first geographic area, and the third house source information is house source information corresponding to the second geographic area; determining a recommended score of each house in the first house information according to the geographic position of each house in the first house information, the at least one house label, and the recommended weight value corresponding to each geographic area, including: when the user type of the target user is the investment type, determining that a recommendation weight value corresponding to the first geographic area is a first recommendation weight value and a recommendation weight value corresponding to the second geographic area is a second recommendation weight value according to the investment type, wherein the first recommendation weight value is larger than the second recommendation weight value; determining a first recommendation score of each house in the second house source information according to the geographic position of each house in the second house source information, the at least one house source label and the first recommendation weight value; determining a second recommendation score of each house in the third house source information according to the geographic position of each house in the third house source information, the at least one house source label and the second recommendation weight value; and determining the recommendation score of each house in the first house source information according to the first recommendation score and the second recommendation score.

In one possible example, the plurality of geographic regions includes a first geographic region and the second geographic region, the first geographic region being different from the second geographic region; the first house source information includes: second house source information and third house source information, wherein the second house source information is house source information corresponding to the first geographic area, and the third house source information is house source information corresponding to the second geographic area; determining a recommended score of each house in the first house information according to the geographic position of each house in the first house information, the at least one house label, and the recommended weight value corresponding to each geographic area, including: when the user type of the target user is the just-needed type, determining that a recommendation weight value corresponding to the first geographic area is a first recommendation weight value and a recommendation weight value corresponding to the second geographic area is a second recommendation weight value according to the just-needed type, wherein the first recommendation weight value is smaller than the second recommendation weight value; determining a first recommendation score of each house in the second house source information according to the geographic position of each house in the second house source information, the at least one house source label and the first recommendation weight value; determining a second recommendation score of each house in the third house source information according to the geographic position of each house in the third house source information, the at least one house source label and the second recommendation weight value; and determining the recommendation score of each house in the first house source information according to the first recommendation score and the second recommendation score.

In one possible example, the determining the first recommendation score of each house in the second house information according to the geographic location of each house in the second house information, the at least one house label, and the first recommendation weight value includes: determining a label score corresponding to each house source label of the at least one house source label according to the geographic position of each house in the second house source information; and according to the label score corresponding to each house source label and the first recommendation weight value, performing weighted calculation to obtain a first recommendation score of each house in the first house source information.

In one possible example, the determining the second recommendation score of each house in the third house information according to the geographic location of each house in the third house information, the at least one house label, and the second recommendation weight value includes: determining a label score corresponding to each house source label of the at least one house source label according to the geographic position of each house in the third house source information; and according to the label score corresponding to each house source label and the second recommendation weight value, performing weighted calculation to obtain a second recommendation score of each house in the third house source information.

The above description has introduced the solution of the embodiment of the present application mainly from the perspective of the method-side implementation process. It is understood that the electronic device comprises corresponding hardware structures and/or software modules for performing the respective functions in order to realize the above-mentioned functions. Those of skill in the art will readily appreciate that the present application is capable of hardware or a combination of hardware and computer software implementing the various illustrative elements and algorithm steps described in connection with the embodiments provided herein. Whether a function is performed as hardware or computer software drives hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

In the embodiment of the present application, the electronic device may be divided into the functional units according to the method example, for example, each functional unit may be divided corresponding to each function, or two or more functions may be integrated into one processing unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit. It should be noted that the division of the unit in the embodiment of the present application is schematic, and is only a logic function division, and there may be another division manner in actual implementation.

Fig. 5 is a block diagram illustrating functional units of a user portrait-based house source pushing apparatus 500 according to an embodiment of the present application. The apparatus 500 comprises:

an obtaining unit 501, configured to obtain user information of a target user, and determine a user type of the target user according to the user information, where the user type is used to indicate an identity feature of the target user;

a first determining unit 502, configured to determine at least one room source tag required by the target user according to the user type;

a second determining unit 503, configured to determine first house source information in a plurality of geographic areas, where the first house source information includes house source information of at least one house;

a third determining unit 504, configured to determine a recommendation score of each house in the first house information according to a geographic location of each house in the first house information, the at least one house label, and a recommendation weight value corresponding to each geographic area;

a sending unit 505, configured to sort, according to the recommendation score, the house source information corresponding to each house in the first house source information, and send the sorted first house source information to the terminal of the target user.

As can be seen, the house source pushing device 500 based on the user representation according to the embodiment of the present application determines the user type of the target user according to the user information by acquiring the user information of the target user; determining at least one house source label required by the target user according to the user type; determining first house source information in a plurality of geographic areas, wherein the first house source information comprises house source information of at least one house; determining a recommended score of each house in the first house source information according to the geographic position of each house in the first house source information, the at least one house source label and the recommended weight value corresponding to each geographic area; and sorting the house source information corresponding to each house in the first house source information according to the recommended scores, and sending the sorted first house source information to the terminal of the target user, so that the matching degree of house sources pushed to the target user can be improved, and the efficiency of searching for proper house sources by the target user is improved.

The user-portrait-based house source pushing apparatus 500 may further include a storage unit 506 for storing program codes and data of the electronic device. The storage unit 506 may be a memory.

In a possible example, in the aspect of determining the user type of the target user according to the user information, the obtaining unit 501 is specifically configured to: determining the user type score of the target user according to the personal information, the work information, the income information and the asset information of the user in the user information; and determining the user type of the target user according to the user type score.

In one possible example, the plurality of geographic regions includes a first geographic region and the second geographic region, the first geographic region being different from the second geographic region; the first house source information includes: second house source information and third house source information, wherein the second house source information is house source information corresponding to the first geographic area, and the third house source information is house source information corresponding to the second geographic area; in the aspect of determining the recommendation score of each house in the first house information according to the geographic location of each house in the first house information, the at least one house label, and the recommendation weight value corresponding to each geographic area, the third determining unit 504 is specifically configured to: when the user type of the target user is the investment type, determining that a recommendation weight value corresponding to the first geographic area is a first recommendation weight value and a recommendation weight value corresponding to the second geographic area is a second recommendation weight value according to the investment type, wherein the first recommendation weight value is larger than the second recommendation weight value; determining a first recommendation score of each house in the second house source information according to the geographic position of each house in the second house source information, the at least one house source label and the first recommendation weight value; determining a second recommendation score of each house in the third house source information according to the geographic position of each house in the third house source information, the at least one house source label and the second recommendation weight value; and determining the recommendation score of each house in the first house source information according to the first recommendation score and the second recommendation score.

In one possible example, the plurality of geographic regions includes a first geographic region and the second geographic region, the first geographic region being different from the second geographic region; the first house source information includes: second house source information and third house source information, wherein the second house source information is house source information corresponding to the first geographic area, and the third house source information is house source information corresponding to the second geographic area; in the aspect of determining the recommendation score of each house in the first house information according to the geographic location of each house in the first house information, the at least one house label, and the recommendation weight value corresponding to each geographic area, the third determining unit 504 is specifically configured to: when the user type of the target user is the just-needed type, determining that a recommendation weight value corresponding to the first geographic area is a first recommendation weight value and a recommendation weight value corresponding to the second geographic area is a second recommendation weight value according to the just-needed type, wherein the first recommendation weight value is smaller than the second recommendation weight value; determining a first recommendation score of each house in the second house source information according to the geographic position of each house in the second house source information, the at least one house source label and the first recommendation weight value; determining a second recommendation score of each house in the third house source information according to the geographic position of each house in the third house source information, the at least one house source label and the second recommendation weight value; and determining the recommendation score of each house in the first house source information according to the first recommendation score and the second recommendation score.

In a possible example, in the aspect of determining the first recommendation score of each house in the second house information according to the geographic location of each house in the second house information, the at least one house label, and the first recommendation weight value, the third determining unit 504 is specifically configured to: determining a label score corresponding to each house source label of the at least one house source label according to the geographic position of each house in the second house source information; and according to the label score corresponding to each house source label and the first recommendation weight value, performing weighted calculation to obtain a first recommendation score of each house in the first house source information.

In a possible example, in the aspect of determining the second recommendation score of each house in the third source information according to the geographic location of each house in the third source information, the at least one source label, and the second recommendation weight value, the third determining unit 504 is specifically configured to: determining a label score corresponding to each house source label of the at least one house source label according to the geographic position of each house in the third house source information; and according to the label score corresponding to each house source label and the second recommendation weight value, performing weighted calculation to obtain a second recommendation score of each house in the third house source information.

Embodiments of the present application also provide a computer storage medium, where the computer storage medium stores a computer program for electronic data exchange, the computer program enabling a computer to execute part or all of the steps of any one of the methods described in the above method embodiments, and the computer includes an electronic device.

Embodiments of the present application also provide a computer program product comprising a non-transitory computer readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps of any of the methods as described in the above method embodiments. The computer program product may be a software installation package, the computer comprising an electronic device.

It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present application is not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required in this application. In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.

In the embodiments provided in the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the above-described division of the units is only one type of division of logical functions, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of some interfaces, devices or units, and may be an electric or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

The integrated unit may be stored in a computer readable memory if it is implemented in the form of a software functional unit and sold or used as a stand-alone product. Based on such understanding, the technical solution of the present application may be substantially implemented or a part of or all or part of the technical solution contributing to the prior art may be embodied in the form of a software product stored in a memory, and including several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the above-mentioned method of the embodiments of the present application. And the aforementioned memory comprises: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.

Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by associated hardware instructed by a program, which may be stored in a computer-readable memory, which may include: flash Memory disks, Read-Only memories (ROMs), Random Access Memories (RAMs), magnetic or optical disks, and the like.

The foregoing detailed description of the embodiments of the present application has been presented to illustrate the principles and implementations of the present application, and the above description of the embodiments is only provided to help understand the method and the core concept of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.

Claims

1. A user portrait based house source pushing method is characterized by comprising the following steps:

2. The method of claim 1, wherein the determining the user type of the target user according to the user information comprises:

determining the user type score of the target user according to the personal information, the work information, the income information and the asset information of the user in the user information;

and determining the user type of the target user according to the user type score.

3. The method according to any of claims 1-2, wherein the user types include: investment type and or on demand type.

4. The method of claim 3, wherein the plurality of geographic regions comprises a first geographic region and the second geographic region, the first geographic region being different from the second geographic region; the first house source information includes: second house source information and third house source information, wherein the second house source information is house source information corresponding to the first geographic area, and the third house source information is house source information corresponding to the second geographic area;

determining a recommended score of each house in the first house information according to the geographic position of each house in the first house information, the at least one house label, and the recommended weight value corresponding to each geographic area, including:

when the user type of the target user is the investment type, determining that a recommendation weight value corresponding to the first geographic area is a first recommendation weight value and a recommendation weight value corresponding to the second geographic area is a second recommendation weight value according to the investment type, wherein the first recommendation weight value is larger than the second recommendation weight value;

determining a first recommendation score of each house in the second house source information according to the geographic position of each house in the second house source information, the at least one house source label and the first recommendation weight value;

determining a second recommendation score of each house in the third house source information according to the geographic position of each house in the third house source information, the at least one house source label and the second recommendation weight value;

and determining the recommendation score of each house in the first house source information according to the first recommendation score and the second recommendation score.

5. The method of claim 3, wherein the plurality of geographic regions comprises a first geographic region and the second geographic region, the first geographic region being different from the second geographic region; the first house source information includes: second house source information and third house source information, wherein the second house source information is house source information corresponding to the first geographic area, and the third house source information is house source information corresponding to the second geographic area;

when the user type of the target user is the just-needed type, determining that a recommendation weight value corresponding to the first geographic area is a first recommendation weight value and a recommendation weight value corresponding to the second geographic area is a second recommendation weight value according to the just-needed type, wherein the first recommendation weight value is smaller than the second recommendation weight value;

determining a second recommendation score of each house in the third house source information according to the geographic position of each house in the third house source information, the at least one house source label and the second recommendation weight value; and determining the recommendation score of each house in the first house source information according to the first recommendation score and the second recommendation score.

6. The method of any one of claims 4-5, wherein determining the first recommendation score for each house in the second room source information according to the geographic location of each house in the second room source information, the at least one room source label, and the first recommendation weight value comprises:

determining a label score corresponding to each house source label of the at least one house source label according to the geographic position of each house in the second house source information;

and according to the label score corresponding to each house source label and the first recommendation weight value, performing weighted calculation to obtain a first recommendation score of each house in the first house source information.

7. The method according to any one of claims 4-5, wherein said determining a second recommendation score for each house in said third feed information according to a geographic location of each house in said third feed information, said at least one feed label, and said second recommendation weight value comprises:

determining a label score corresponding to each house source label of the at least one house source label according to the geographic position of each house in the third house source information;

and according to the label score corresponding to each house source label and the second recommendation weight value, performing weighted calculation to obtain a second recommendation score of each house in the second house source information.

8. A house source pushing device based on user portrait, the device comprising:

9. An electronic device comprising a processor, a memory, a communication interface, and one or more programs stored in the memory and configured to be executed by the processor, the programs comprising instructions for performing the steps in the method of any of claims 1-7.

10. A computer-readable storage medium, characterized in that it stores a computer program for electronic data exchange, wherein the computer program causes a computer to perform the method according to any one of claims 1-7.