WO2018090788A1 - 租赁对象属性值调整方法、装置及服务器 - Google Patents

租赁对象属性值调整方法、装置及服务器 Download PDF

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Publication number
WO2018090788A1
WO2018090788A1 PCT/CN2017/107300 CN2017107300W WO2018090788A1 WO 2018090788 A1 WO2018090788 A1 WO 2018090788A1 CN 2017107300 W CN2017107300 W CN 2017107300W WO 2018090788 A1 WO2018090788 A1 WO 2018090788A1
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WIPO (PCT)
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user
value
credit
application platform
friend
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PCT/CN2017/107300
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English (en)
French (fr)
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刘日佳
刘志斌
郑博
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腾讯科技(深圳)有限公司
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Publication of WO2018090788A1 publication Critical patent/WO2018090788A1/zh

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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce
    • G06Q30/06Buying, selling or leasing transactions
    • G06Q30/0645Rental transactions; Leasing transactions
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce
    • G06Q30/06Buying, selling or leasing transactions

Definitions

  • the present application relates to the field of data processing technologies, and in particular, to adjustment of attribute values of lease objects.
  • the rise of rental platforms such as renting cars and renting houses has provided convenience for users in all aspects of life and work.
  • the user can browse information on rental objects such as houses and vehicles on the rental platform, and decide whether to rent a rental object on the rental platform.
  • the information of the leased object can be browsed on the rental platform.
  • the user pays more attention to the attribute value of the leased object in the information of the leased object, and determines whether to rent the leased object by browsing the attribute value of the leased object.
  • the user can browse the rental information on the rental platform and focus on the rental price (ie, the property value of the rental house), and decide to rent the house when the rental price of the house meets expectations.
  • the attribute value of the leasing object is generally priced according to the difference in demand, that is, the corresponding attribute value is usually set in consideration of the market supply and demand relationship, for example, in a rental platform or a hotel-type hotel reservation platform. On the Saturday and Sunday, the rental price is higher than the working day. Obviously, the adjustment of the property value of this rental object is not flexible enough.
  • the embodiment of the present invention provides a method, a device, and a server for adjusting an attribute value of a leased object, so as to improve the flexibility and intelligence of adjusting the attribute value of the leased object in the leased platform.
  • a method for adjusting a leased object attribute value includes:
  • the lease object browsing request is used to request information of at least one lease object on the first application platform;
  • the method for adjusting the attribute value of the leased object obtains the lease of the first user by acquiring the credit user of the first user and the credit score of the second user as the second user of the first user on the second application platform.
  • the attribute value of the object is adjusted, and the credit score of the first user and the credit score of the second user can reflect the first The degree of credit of the user, so that the attribute value of the leased object can be flexibly and intelligently adjusted according to the credit level of the tenant.
  • the second user that determines the friend relationship with the first user on the second application platform includes:
  • the ratio of the first value to the second value is positively correlated with the credit score of the first user and the credit of the second user.
  • determining, according to the relationship chain, the second user that is in a friend relationship with the first user on the second application platform includes:
  • the second user is a close friend of the first user, and the social concern of the first user is closer, and the credit level of the first user can be more appropriately reflected. Then, the intimacy of the first user is utilized. The credit score of the friend and the credit score of the first user to comprehensively characterize the credit level of the first user will be more reliable.
  • determining a candidate friend user that is a direct friend relationship with the first user includes:
  • Obtaining historical interaction data of the first user and each candidate friend user on the second application platform according to the account of the first user in the second application platform includes:
  • Determining the intimacy of the first user and each candidate friend user according to the historical interaction data of the first user and each candidate friend user includes:
  • selecting the second user whose intimacy meets the set intimacy condition includes:
  • selecting at least one candidate friend user that has the highest affinity with the first user from each selected community, and obtaining m second users includes:
  • one candidate friend user with the highest affinity to the first user is selected.
  • the second user is limited to select from the community where the first user is located, select the second user in the different community, and obtain the second user who has a different social relationship with the first user.
  • the credit score is used to comprehensively reflect the credit level of the first user in the multi-media relationship, and the credit level of the first user is more accurate.
  • adjusting the attribute value of the leased object from the first value to the second value according to the credit score of the first user and the credit score of the second user includes:
  • the attribute value of the leased object is adjusted from the first value to the second value according to the credit score of the first user, the credit distribution of the second user, the user attribute of the first user, and the object attribute of the leased object.
  • adjusting the attribute value of the leased object from the first value to the second value according to the credit score of the first user and the credit score of the second user includes:
  • the attribute value of the leased object is determined according to the credit score of the first user, the credit distribution of the m second users, the credit distribution of all the buddy users of the first user, the user attribute of the first user, and the object attribute of the leased object.
  • the first value is adjusted to the second value.
  • adjusting the attribute value of the leased object from the first value to the second value according to the credit score of the first user and the credit score of the second user includes:
  • the ratio of the set credit threshold to the integrated credit score shown is multiplied by the first value of the lease object to determine the second value of the lease object.
  • the attribute value of the rental object is adjusted based on the credit score of the first user and the credit distribution of the second user on the second application platform.
  • the credit distribution of the second user in the second application platform is to display the credit level of the second user through a large amount of data, and can express the credit level of the second user from a more macro perspective, and combine the credit of the first user. The ability to synthesize the credit level of the first user more intelligently.
  • a second aspect of the present invention provides a rental object attribute value adjustment apparatus, including:
  • the request acquisition module is configured to obtain a lease object browsing request sent by the client; the lease object browsing request is used for Requesting information of at least one rental object on the first application platform;
  • a second user determining module configured to determine, according to an account of the first user in the second application platform, a second user that is in a friend relationship with the first user on the second application platform;
  • a credit score obtaining module configured to obtain credits of the first user and the second user in the second application platform according to the account of the first user and the second user in the second application platform;
  • the attribute value adjustment module is configured to adjust the attribute value of the lease object from the first value to the second value according to the credit score of the first user and the credit score of the second user; wherein the first value of the lease object is from the first The application platform's attribute value database is retrieved;
  • the attribute value feedback module is configured to feed back the rental object browsing page to the client, and the attribute value of the rental object in the rental object browsing page is the second value. .
  • the second user determining module includes:
  • a relationship chain obtaining sub-module configured to acquire a relationship chain of the first user in the second application platform according to the account of the first user in the second application platform; wherein the first user logs in the first account with the account in the second application platform Application platform
  • the second user determining submodule is configured to determine, according to the relationship chain, a second user who is a friend relationship with the first user in the second application platform.
  • the ratio of the first value to the second value is positively correlated with the credit score of the first user and the credit share of the second user.
  • the second user determining sub-module is configured to determine, according to the relationship chain, a second user that is in a friend relationship with the first user on the second application platform, and specifically includes:
  • a first determining unit configured to determine, according to the relationship chain, a candidate friend user that is a direct friend relationship with the first user
  • a first acquiring unit configured to acquire historical interaction data of the first user and each candidate friend user on the second application platform according to the account of the first user in the second application platform;
  • a second determining unit configured to determine, according to historical interaction data of the first user and each candidate friend user, the intimacy of the first user and each candidate friend user;
  • the selecting unit is configured to select, from each candidate friend user, a second user whose intimacy meets the set intimacy condition.
  • the first determining unit includes:
  • a first obtaining sub-unit configured to acquire community information of the first user in the second application according to the account of the first user in the second application platform, and select k communities from the community of the first user;
  • a first determining subunit configured to determine a candidate friend user who is a direct friend relationship with the first user from the selected communities according to the relationship chain;
  • the first obtaining unit includes:
  • a second obtaining sub-unit configured to acquire historical interaction data of each candidate friend user in the selected community according to the account of the first user in the second application platform;
  • the second determining unit comprises:
  • a second determining subunit configured to perform mutual history according to the first user and each candidate friend user in each selected community Dynamic data, determining the intimacy of the first user and each candidate friend user in each selected community;
  • the sub-units are selected to select at least one candidate friend user with the highest affinity from the first user from the selected communities to obtain m second users, where m is greater than k.
  • the subunits are selected, including:
  • a first selecting sub-unit configured to select, from a community in which the candidate user with the highest affinity of the first user is located, the first m-k+1 candidate friend users with the highest affinity to the first user;
  • the second selection sub-unit is configured to select one candidate friend user with the highest affinity from the first user from the remaining k-1 communities.
  • the attribute value adjustment module is configured to adjust the attribute value of the lease object from the first value to the second value according to the credit score of the first user and the credit score of the second user, specifically including :
  • the attribute value of the leased object is adjusted from the first value to the second value according to the credit score of the first user, the credit distribution of the second user, the user attribute of the first user, and the object attribute of the leased object.
  • the attribute value adjustment module includes:
  • a credit sub-determination sub-module configured to determine a credit distribution of the m second users, and a credit distribution of all the friend users of the first user
  • the attribute value adjustment submodule is configured to use, according to the credit score of the first user, the credit distribution of the m second users, the credit distribution of all the friends of the first user, the user attribute of the first user, and the object attribute of the leased object. And adjust the attribute value of the leased object from the first value to the second value.
  • the attribute value adjustment module includes:
  • the comprehensive sub-module is configured to integrate the credit score of the first user with the credit of the second user to obtain a comprehensive credit score
  • the calculation submodule is configured to multiply the ratio of the set credit threshold to the integrated credit score, multiply the first value of the lease object, and determine the second value of the lease object.
  • the above-mentioned rental object attribute value adjusting device corresponds to the method embodiment, and the effect achieved is also consistent, and details are not described herein again.
  • a third aspect of the present invention provides a server including the above-described rental object attribute value adjusting means.
  • a method for adjusting a leased object attribute value is provided, which is applied to a server, and the method includes:
  • the server determines, according to the account of the first user in the second application platform, a second user that is in a friend relationship with the first user on the second application platform;
  • the server adjusts the attribute value of the lease object from a first value to a second value according to the credit score of the first user and the credit score of the second user; wherein, the first value of the lease object is from Retrieving from the attribute value database of the first application platform;
  • the server feeds back the lease object browsing page to the client, and the attribute value of the lease object in the lease object browsing page is the second value.
  • the fifth aspect of the present invention further provides a lease object attribute value adjustment device, where the device includes:
  • a memory for storing program code and transmitting the program code to the processor
  • a processor configured to execute the foregoing lease object attribute value adjustment method according to an instruction in the program code.
  • a storage medium configured to store program code, and the program code is configured to execute the foregoing lease object attribute value adjustment method.
  • a computer program product comprising instructions which, when run on a computer, cause the computer to perform the above-described rental object attribute value adjustment method.
  • the server determines the second user who is in the friend relationship with the first user on the second application platform;
  • the attribute value of the leased object is adjusted based on the credit scores of the first user and the second user on the second application platform, and the attribute value of the corresponding leased object is fed back to the client for the second value. Therefore, the present invention adopts the credit score of the first user and the credit score of the second user who is a friend relationship with the first user to comprehensively reflect the credit level of the first user, and the obtained comprehensive credit level of the first user can be further improved.
  • the credit status of the first user is comprehensively and authoritatively characterized. Therefore, the attribute value of the lease object is adjusted according to the credit score of the first user and the credit score of the second user, so as to flexibly and intelligently adjust the attribute value of the lease object.
  • FIG. 1 is a schematic structural diagram of a system for implementing a method for adjusting a leased object attribute value according to an embodiment of the present invention
  • FIG. 2 is a signaling flowchart of a method for adjusting a leased object attribute value according to an embodiment of the present invention
  • FIG. 3 is a schematic diagram of a user operation triggering a client to send a rental object browsing request according to an embodiment of the present invention
  • FIG. 4 is a schematic diagram of an application scenario of a method for adjusting a leased object attribute value according to an embodiment of the present invention
  • FIG. 5 is a schematic diagram showing an application scenario effect of a method for adjusting a leased object attribute value according to an embodiment of the present invention
  • FIG. 6 is a flow chart showing an implementation method of determining a second user according to an embodiment of the present invention.
  • FIG. 7 is a schematic diagram of a community of users in a method for adjusting a leased object attribute value according to an embodiment of the present invention.
  • FIG. 8 is a flowchart of another implementation method for determining a second user according to an embodiment of the present invention.
  • FIG. 9 is a flowchart of a method for adjusting an attribute value of a leased object according to an embodiment of the present invention.
  • FIG. 10 is a schematic diagram of another application scenario of a method for adjusting a leased object attribute value according to an embodiment of the present invention.
  • FIG. 11 is a block diagram showing the structure of a rental object attribute value adjusting apparatus according to an embodiment of the present invention.
  • FIG. 12 is a block diagram showing the hardware structure of a server according to an embodiment of the present invention.
  • the rental market has become increasingly popular, especially for renting cars and renting houses, which has brought a lot of convenience to people.
  • What follows is the increasing number of leasing platforms, leasing objects, and tenants.
  • the current problem is that for the rental platform, the attribute value of the lease object is generally priced according to the difference in demand, and the method of adjusting the pricing is too single and not flexible enough. For example, on the rental platform, the rental price on Saturday and Sunday will be higher than the working day. Obviously, the adjustment of the attribute value of this rental object is not flexible enough.
  • the embodiment of the present application provides a method, a device, and a server for adjusting an attribute value of a leased object, and renting according to the credit scores of the first user and the second user on the second application platform.
  • the attribute values of the objects are adjusted to flexibly and intelligently adjust the attribute values of the leased objects.
  • FIG. 1 is a system architecture diagram of a method for adjusting a leased object attribute value according to an embodiment of the present invention.
  • the system architecture may include: a client 10, a server 20, a relational database 30, an attribute value database 40, and a credit database. 50.
  • the server 20 and the attribute value data 40 belong to the first application platform; the relational database 30 and the credit information database 50 belong to the second application platform; the first application platform and the second application platform are different application platforms, but the first application platform may
  • the account of the second application platform is accessed, for example, the user can log in to the first application platform by using the account of the second application platform.
  • the first application platform and the second application platform may also be the same application platform, and the second application platform can provide the rental service provided by the first application platform.
  • the first application platform may be a rental platform
  • the second application platform may be a social network service (SNS) platform
  • the user may log in to the rental platform through the account of the SNS platform; It can also be linked to the rental platform through the SNS platform.
  • SNS social network service
  • the client 10 can be loaded on a user device such as a smart phone, a tablet computer, a notebook computer, and the like, and communicates with the server 20.
  • the user can access the server 20 through the client 10 and request to browse the rental object.
  • the client 10 may be a separately developed client that cooperates with the server 20; the user may download the client to the user device locally through the APP STORE or the application official website.
  • the client can also be in the form of a browser.
  • the client 10 may also be a client of the second application platform.
  • the user may be allowed to pass the client of the second application platform. Linking with the first application platform, entering the page corresponding to the first application platform.
  • the server 20 is a service device in a server cluster to which the first application platform belongs, and is set on the network side.
  • the server 20 is mainly used for data processing, and intelligently adjusts according to different browsing browsing users.
  • the attribute value of the leased object is mainly used for data processing, and intelligently adjusts according to different browsing browsing users.
  • the relational database 30 is a database for recording each user relationship chain in the second application platform, and a user's relationship chain is used to indicate the relationship between the user and the friend on the second application platform, and the relationship database 30 can determine that each user is in the first The friend of the application platform; in the specific implementation, the second application platform may be an SNS application platform.
  • the attribute value database 40 is a database in which the value of each leased object attribute is recorded in the first application platform, for example, the initial attribute value of the leased object is recorded.
  • the server 20 may obtain the initial attribute value of the leased object from the attribute value database 40 when the user requests to browse the leased object, and adjust the initial attribute value of the leased object by using the method provided by the embodiment of the present invention.
  • the credit information database 50 is a database in which the credit scores of the users are recorded in the second application platform.
  • the credit score of the user is a score for measuring the credit level of the user according to the behavior data of the financial, network social, etc. of the user historical time period; the credit score of the user predicts the probability that the user will repay the loan on time in the future period, Or the probability of debt default. The higher the user's credit score, the higher the user's credit rating.
  • the credit score of the user can obtain a model for predicting user credit by training a large amount of user credit data, and import behavior data of the user in finance, network socialization, etc. into the above model, and calculate the credit score of the user.
  • the server 20 can obtain the credit scores of each user through the open interface of the credit information database 50.
  • the credit information database 50 can be a credit information database of the bank credit information database or other open query users.
  • a credit data database for SNS platforms with big data capabilities for SNS platforms with big data capabilities.
  • the server 20 may display different attribute values of the lease object for different users requesting to browse the lease object in the lease object browsing page, so as to provide different users with the purpose of distinguishing the attribute values of the lease object;
  • the server 20 can browse the credit score of the user of the leased object in the second application platform according to the current request, and the credit score of the friend user of the second application platform on the second application platform, and flexibly adjust the attribute value of the leased object. Smart adjustment.
  • FIG. 2 is a signaling flow of a method for adjusting a leased object attribute value according to an embodiment of the present invention, where the method may include:
  • step S10 the client sends a lease object browsing request to the server.
  • the client can be operated by the first user.
  • the client may send a lease object browsing request to the server based on the operation of the first user; if the client detects an operation triggered by the first user and requests an instruction to enter the rental object browsing page, the client sends a lease object browsing to the server. request.
  • the rental object browsing page is a page for displaying a rental object, such as a house rental page, a vehicle rental page, etc., and the page generally displays the attribute value of the rental object in addition to the rental object.
  • the server can apply the method provided by the embodiment of the present invention to adjust the displayed house rent.
  • Step S11 The server acquires a relationship chain of the first user in the second application platform according to the account of the first user on the second application platform.
  • the first application platform can access the account of the second application platform, and the user can log in to the first application platform by using the account of the second application platform.
  • the first user may send a login request to the server of the first application platform, which may be a request for the first user to log in to the first application platform in the account of the second application platform; the server is verifying After the adoption, the first user can log in to the first application platform by using the account of the second application platform.
  • the second application platform includes a relational database, where the relationship database records the relationship between each user of the second application platform and the second application platform.
  • the server of the first application platform after determining the account of the first user in the second application platform, may query the relationship chain corresponding to the account of the first user in the second application platform through the open interface of the relational database in the second application platform. Obtaining a relationship chain of the first user on the second application platform.
  • the relationship chain is used to record the relationship pair of the first user on the second application platform, and the friend of the first user on the second application platform may be determined based on the relationship chain of the first user.
  • the relationship chain of the first user may also record a user identifier (such as a user account) of the second user in the second application platform that is a friend relationship with the first user, that is, the relationship chain may be used by each user in the second
  • the user ID of the application platform is connected by the relationship between users to form a chain representing the relationship between users.
  • Step S12 The server determines, according to the foregoing relationship chain, a second user that is in a friend relationship with the first user on the second application platform.
  • the second user may be all the friend users who are friends with the first user in the second application platform, or may be selected from the first user in all the friend users of the second application platform.
  • the user is a close friend.
  • the number of the determined second users is at least one.
  • the second user that is in the buddy relationship with the first user in the second application platform may be configured to use other implementation manners, for example, on the first application platform, in addition to the implementation of the relationship chain in the foregoing steps S11 and S12. And storing a correspondence between the account of the first user and the second user, where the second user is a friend user of the first user on the second application platform. Then, the first user can directly search for the user who is a friend relationship with the first user on the second application platform, the second user, on the first application platform.
  • Step S13 The server obtains the credit scores of the first user and the second user in the second application platform according to the account of the first user and the second user in the second application platform.
  • the credit information database of the second application platform is used to record the credit scores of the users of the second application platform on the second application platform.
  • the credit information database stores the user account and the user's account. The correspondence of credit scores.
  • the server obtains the credit score of the first user in the second application platform according to the account of the first user in the second application platform through the open interface of the second application platform, and the server is based on the second user in the second application platform.
  • the account number is obtained through the open interface of the second application platform credit information database, and the credit score of the second user in the second application platform is obtained.
  • Step S14 The server adjusts the attribute value of the lease object from the first value to the second value according to the credit score of the first user and the credit score of the second user.
  • the first value is recorded in the attribute value database of the first application platform, and is an initial attribute value of the lease object, and the initial attribute value is an attribute value preset to the lease object. Therefore, the server may obtain the initial attribute value of the leased object from the attribute value database of the first application platform - the first value.
  • the server may obtain the adjusted attribute value corresponding to the first user, the second value, by using a pre-established model for predicting the user credit according to the credit score of the first user and the credit score of the second user. Therefore, the initial attribute value of the lease object is adjusted by using the second value, that is, the attribute value of the lease object is adjusted from the first value to the second value, and the lease object adjusted by the credit degree of the first user and the second user is realized.
  • Property value
  • the ratio of the first value to the second value is positively correlated with the credit score of the first user and the credit of the second user; that is, the higher the credit score of the first user and the second user, indicating that the first The larger the ratio of the value to the second value, the smaller the second value after the adjustment of the lease object; the lower the credit score of the first user and the second user, indicating that the smaller the ratio of the first value to the second value, the lease The second value after the object is adjusted is larger.
  • the rental object is the rented house
  • the property value of the lease object is the rent of the house
  • the initial rent - the first value is a fixed value
  • the first user and the second user The higher the credit score, the greater the ratio of the first value to the second value, then the rent of the adjusted house - the second value as the denominator, the smaller; otherwise, the credit score of the first user and the second user
  • the lower the ratio the smaller the ratio of the first value to the second value is required, and the rent of the adjusted house, the second value, is the denominator. It can be seen that for users with high credit level, the attribute value of the smaller lease object is displayed, and the attribute value of the larger lease object is displayed for the user with lower credit degree.
  • the embodiment of the present invention not only adjusts the attribute value of the leased object by browsing the credit score of the first user of the lease object, but also considers the credit score of the second user who is a friend relationship with the first user.
  • the evaluation of the credit level of the first user is more true and accurate; according to the credit scores of the first user and the second user, the adjusted rental object
  • the attribute value will also be closer to the credit level of the first user, and the adjusted attribute value of the rental object and the credit level of the first user are also better matched.
  • the attribute value of the lower lease object By feeding back the attribute value of the lower lease object to the user with higher credit level, the possibility that the owner of the lease object finds the tenant with high credit can be improved; on the contrary, by giving feedback to the user with lower credit degree
  • the attribute value of the high lease object can evade the low credit tenant for the owner of the lease object and reduce the risk of the owner of the lease object during the lease process.
  • step S15 the server feeds back the lease object browsing page to the client, where the attribute value of the lease object in the lease object browsing page is the second value.
  • the attribute value of the leased object is a second value, so that the first user can perform the attribute information of the leased object.
  • Targeted browsing the second value of the leased object may be fed back to the user in other manners, and details are not described herein again.
  • the server may determine the relationship chain of the first user in the second application platform, and determine the relationship chain based on the relationship chain. a second user who is in a friend relationship with the first user on the second application platform; thereby adjusting the attribute value of the lease object based on the credit scores of the first user and the second user on the second application platform, to obtain an attribute value
  • the second value of the rental object and feedback the adjusted rental object browsing page to the client; when the user browses the rental object, based on the credit degree of the user and his friend, the user is provided with flexible and intelligent adjustment of the attribute value of the rental object. After the rental object browses the page.
  • the credit score of the user who browses the lease object and the credit score of the second user who is a friend relationship with the user are used to comprehensively reflect the credit degree of the user, and the lease is based on the comprehensive credit degree of the user.
  • the attribute value of the object is intelligently adjusted, and the corresponding rental object browsing page is fed back to the user, and the flexibility and intelligence of adjusting the attribute value of the rented object in the rental object browsing page is improved.
  • the method for adjusting the rental object attribute value provided by the embodiment of the present invention can be applied to the adjustment of the rental price of the house.
  • the rental price of the house is performed. Adjustment.
  • FIG. 4 is a schematic diagram of an application of a rental object attribute value adjustment method in a rental platform provided by an embodiment of the present invention
  • the first user logs in to the rental platform through the client and the account of the SNS platform;
  • the client After the first user logs in to the rental platform through the client, when the first user requests the house rental page by using the client, the client sends a housing rental page request to the server;
  • the server may determine the house currently renting on the rental platform, and obtain the historical rent of the house from the database of the rental platform;
  • the server can use the account of the first user on the SNS platform to query the relationship chain of the first user on the SNS platform from the relational database of the SNS platform;
  • the server determines, according to the relationship chain, a second user who is a friend relationship with the first user on the SNS platform, and determines an account of the second user on the SNS platform from the relationship chain;
  • the server retrieves the credit score of the first user and the credit score of the second user from the credit information database of the SNS platform;
  • the server adjusts the historical rent of each house according to the credit score of the first user and the credit score of the second user; wherein, the ratio of the historical rent of each house to the adjusted rent, and the credit score of the first user and the second user
  • the credit is divided into positive correlations; that is, when the historical rent of the house is a fixed value, the higher the credit score of the first user and the second user, the lower the adjusted rent of the house, the first user and the second user The lower the credit score, the higher the rent of the adjusted house;
  • the server will feedback the rental page of the house after adjusting the rent of the house to the client.
  • the application effect diagram shown in FIG. 5 is obtained by using the rental object attribute value adjustment method provided by the embodiment of the present invention.
  • the client The content shown above is: the historical rent of the house (the original rent shown in Figure 5), and the adjusted rent (indicating the credit offer shown in Figure 5) in combination with the credits of the first user and his friend. It can be seen that in the case that the credit degree of the first user and his friend user is relatively high, the rent after the adjustment of the house is decreased.
  • the rental object attribute value adjustment method provided by the embodiment of the present invention can also be applied to other rental scenarios of rented items such as renting a house and renting a car. Specifically, based on the credit scores of the users and their friends, the credit level of the user is comprehensively reflected, and the attribute value of the rental object is flexibly and intelligently adjusted based on the comprehensive credit level of the user, and the users with high credit, houses, vehicles, etc.
  • the rent of idle items can be reduced, attracting users with high credit, and enabling the lessor to find a satisfactory tenant; and for users with low credit, it can increase rent, reduce the rental risk of the lessor, and make idle items such as houses and vehicles. Can be used reasonably.
  • step S12 shown in FIG. 1 is When determining the second user who is a friend relationship with the first user, it may be determined that the first user's close friend is the second user.
  • FIG. 6 shows a flowchart of a method for determining a second user who is a close friend relationship with a first user, the method being applicable to a server.
  • the method includes:
  • Step S20 The server determines, according to the relationship chain, a candidate friend user who is a direct friend relationship with the first user.
  • the relationship chain of the first user indicates the friend user who is a friend relationship with the first user; and the relationship between the friend user and the first user in the relationship chain can be measured by “degree”; degree refers to the relationship chain
  • degree refers to the relationship chain
  • the connection relationship in the connection diagram once a friend thinks it is a direct friend, a second friend thinks it is a friend of a friend, and so on.
  • a friend user who is a friend of the first user that is, a direct friend of the first user, is determined from the relationship chain of the first user, and the determined friend user is used as a candidate friend user.
  • Step S21 The server acquires historical interaction data of the first user and each candidate friend user on the second application platform according to the account of the first user in the second application platform.
  • Step S22 The server determines the intimacy between the first user and each candidate friend user according to the historical interaction data of the first user and each candidate friend user.
  • the intimacy of the first user and the candidate friend user may be determined by the number of interactions between the first user and the candidate friend user in the set historical time period, and the first user and the candidate friend user are in the set historical time period. The more the number of interactions within the first user, the higher the intimacy of the first user and the candidate friend user; that is, the number of interactions between the first user and the candidate friend user in the set historical time period, and the intimacy between the first user and the candidate friend user Degree is positively related.
  • the number of interactions between the first user and a candidate friend may include: the number of times the first user receives the candidate friend's single chat message, the number of times the first user sends the single chat message to the candidate friend, and the candidate friend is The friend circle comments on the number of times the content posted by the first user, at least one of the number of times the first user and the candidate friend user comment each other in the circle of friends, and the like.
  • the server may obtain the number of interactions between the first user and the candidate friend user from the database of the second application platform by using the account of the first user on the second application platform.
  • the intimacy of the user and each candidate friend user may be calculated according to the number of interactions between the user and the friend user by using a machine learning method, and the corresponding mathematical model is learned; according to the first user and each candidate friend user The number of interactions, through the mathematical model constructed, calculates the intimacy of the first user and each candidate.
  • the function F the formula for calculating the intimacy Q of the first user U and the candidate friend user M can be as follows:
  • step S23 the server selects, from among the candidate friend users, the second user whose intimacy meets the set intimacy condition.
  • the second user determined to be in a friend relationship with the first user on the second application platform determined in step S12 is determined to be the second user.
  • the second user determined in step S12 is not limited to the friend user who meets the set intimacy condition with the intimacy of the first user, but all the friend users who are in a friend relationship with the first user.
  • the second user whose intimacy meets the set intimacy condition is the most intimate m buddy users among the candidate buddy users (m is a set value); in specific implementation, according to the intimacy from large to small In order, the candidate friend users are sorted, and the friend user ranked in the first m position is selected as the second user.
  • step S13 and step S14 shown in FIG. 2 can be implemented according to the second user selected in step S23.
  • the first user U of the same community represents the same way as the friends in the community, and the aggregation coefficient of the user in the community
  • the direct friend of the first user U can be divided into three communities, and the type of the community usually represents the first user U and the friends in the community.
  • the community A may be the colleague community of the first user U, where A1 and A2 are first friends of the first user U (direct friends), and A3 is the second friend of the first user U (friends) Friend);
  • Community B may be the community of friends and relatives of the first user U, where B1 and B2 are first friends of the first user U;
  • community C may be the classmate community of the first user U, wherein C1 is the first One user U's one-time friend, C2 is the second user of the first user U (friend's friend).
  • the second may be considered.
  • FIG. 8 another optional method for determining a second user that is a friend relationship with the first user is provided.
  • the method is applicable to the server, including:
  • Step S30 The server acquires community information of the first user in the second application according to the account of the first user in the second application platform, and selects k communities of the first user.
  • k is the set number of communities, and may be all communities of the first user, or may be part of the community of the first user.
  • the community type and the number of communities may be preset, and at least one community type corresponding to the community type corresponding to the community type is selected from the community of the first user. And randomly select the remaining number of communities from the remaining communities.
  • the community type may be a community type closely related to the first user, such as a community of friends and relatives, a classmate community, etc., and the first user has a close relationship with the first user due to the community composed of interests and interests. Degree, obviously lower than the first user's relatives and friends community, classmates community.
  • Step S31 The server determines, according to the relationship chain of the first user, a candidate friend user who is a direct friend relationship with the first user from the selected communities.
  • a friend user who is a friend of the first user may be determined from each community of the k communities of the first user.
  • step S30 and step S31 are an implementation of the step S20 in the embodiment of the present invention shown in FIG. 6 in the community scenario.
  • Step S32 The server acquires historical interaction data of the first user and each candidate friend user in each selected community according to the account of the first user in the second application platform.
  • step S32 is an implementation manner in the community scenario in step S21 in the embodiment of the present invention shown in FIG. 6.
  • Step S33 The server determines, according to historical interaction data of the first user and each candidate friend user in each selected community, the intimacy of the first user and each candidate friend user in each selected community.
  • step S33 is an implementation of the step S22 in the embodiment of the present invention shown in FIG. 6 in the community scenario.
  • Step S34 The server selects at least one candidate friend user with the highest affinity from the first user from the selected communities, and obtains m second users who are friends with the first user.
  • step S34 is an implementation of the step S23 in the embodiment of the present invention shown in FIG. 6 in the community scenario.
  • At least one candidate friend user with the highest affinity with the first user is selected from each community of the determined k communities to form m second users; that is, from k communities
  • Each of the communities selects a candidate friend user as the second user, and constitutes m second users, and the number of second users selected by each community may be at least one.
  • One selection method is: selecting the same number of candidate friend users with the highest affinity from the first user from each community to form m second users. That is, in each community, the candidate friend users of the first user are sorted according to the intimacy with the first user from high to low; then the candidate of the top (m/k) position is selected in each community.
  • the buddy user as the second user, selects m candidate buddy users in the k community, that is, the selected second user.
  • Another selection method is: selecting a plurality of users who are the candidate friends relationship with the first user from the community in which the first user is the most intimate candidate friend user, and then averaging from the remaining other communities.
  • the candidate friend user with the highest affinity with the first user is selected. For example, in each community, the candidate user of the first user is still sorted according to the intimacy with the first user; from the community of the candidate user with the highest affinity to the first user.
  • k community selects a total of m candidate friend users, that is, m second users.
  • a specific selection method is: selecting, in the community where the candidate user with the highest affinity of the first user is located, the first (m-k+1) candidate friend users with the highest affinity with the first user, Then, among the remaining (k-1) communities, the candidate friend users with the highest intimacy with the first user are respectively selected, and m second users who are friends with the first user are obtained.
  • the community and the intimacy of the candidate user of the first user are known.
  • the community with the highest intimacy candidate user of the user has the highest intimacy of 0.9, the corresponding candidate friends are A1 and A2, and they belong to community A; then, the most intimate one is selected from community A.
  • Candidate friend user Community Intimacy with the first user Credit score A1 A 0.9 730 A2 A 0.9 650 B1 B 0.7 600 B2 B 0.6 500 C1 C 0.5 340
  • the adjustment of the attribute value of the rental object can be implemented by using step S12 and step S13 in the embodiment of the present invention shown in FIG. .
  • the embodiment of the present invention may determine the credit distribution of the second user, and adjust the attribute value of the lease object according to the credit score of the first user and the credit distribution of the second user. .
  • a flow chart of a method for adjusting a leased object attribute value according to a credit score of a first user and a credit score of a second user is provided.
  • the method is applicable to a server, including:
  • Step S40 dividing the value range of the credit score into intervals, and determining a plurality of distribution intervals of the credit scores.
  • the value range of the credit score is sent by the second application platform to the first application platform, and the value range between the maximum value and the minimum value is used as the credit score of the first application platform. Ranges.
  • the specific implementation manner for the second application platform to obtain the maximum value and the minimum value of the credit score may be that the second application platform collects the credit score data of the user on the platform, and obtains the maximum value and the minimum value of the credit score; The second application platform only counts the maximum value of the credit score, and the minimum value may be preset by the second application platform; or the second application platform may preset the credit on the second application platform according to the situation of the user on the platform.
  • the maximum and minimum values of the points may be used.
  • the first application platform presets the value range of the credits according to the actual situation from the second application platform, and details are not described herein again.
  • the distribution interval of credit points can satisfy the frequency distribution, the normal distribution, and the like.
  • the credit score corresponding to each distribution interval may be set, so that the value range of the credit score is divided according to the credit scores of each distribution interval, and multiple distribution intervals of the credit scores are obtained. For example, if the credit score has a value range of [300,900) and the credit score of each distribution interval is 100, the value of each credit of the credit score can be divided by 100, which is obtained as shown in Table 3 below.
  • Table 3 The distribution interval of the six credit points shown; wherein the distribution interval of 3 represents a credit score of 100 digits, the distribution interval of 4 represents a credit score of 100 digits, and so on.
  • 3 to 8 in Table 3 can be considered as a binning of the value range of credit scores, and binning refers to a common means of discretizing continuous variables, such as a person aged 0-99.
  • Sub-box processing can be divided into 0-18 years old is a minor, 18-45 is a youth, 45-60 is a middle-aged, 60 or more is an old age.
  • the binning method corresponding to the value range of the credit score is divided by means of the binning means, and a plurality of distribution intervals of the credit score are determined.
  • the binning is not necessarily achieved by dividing the 100-point credit in the value range of the credit by 100. It can also be implemented by other binning methods, and is not specifically limited herein.
  • Step S41 Determine, according to the credit scores of the second users, a distribution interval of credit points in which the credit points of the second users are located, and obtain a credit distribution of the second user.
  • the credit distribution of the second user can represent the overall credit level of the second user. If the credit distribution of the second user mostly falls within the distribution interval of the high credit score, the credit degree of the second user is higher; otherwise, if the credit distribution of the second user mostly falls within the distribution interval of the low credit score. , indicating that the second user has a lower credit rating.
  • the credits of the second users A1, A2, B1, and C1 in the relationship with the first user shown in Table 2 are combined with the credit distribution of the credits shown in Table 3.
  • the credit distribution of the second user may be as follows: Table 4 shows.
  • the manner of determining the second user may be the second user determined by the method shown in FIG. 6 to meet the set intimacy condition of the first user's intimacy; or may be determined by the method shown in FIG.
  • the m second users of the k communities of the first user may also determine that all direct friend users of the first user are the second user in the method shown in FIG. 2;
  • the embodiment of the present invention determines the credit distribution of the second user, which may be determining a credit distribution of the second user that meets the set intimacy condition of the first user, and may also determine the first user.
  • the credit distribution of the m second users of the k communities may also be the credit distribution of all direct friend users of the first user.
  • Step S42 adjusting the attribute value of the leased object from the first value to the second value according to the credit score of the first user, the credit distribution of the second user, the user attribute of the first user, and the object attribute of the leased object.
  • the embodiment of the present invention may be based on the credit score of the first user, the credit distribution of the second user, the user attribute of the first user, the object attribute of the leased object, and the initial
  • the first value (initial attribute value) adjusts the attribute value of the leased object.
  • the attribute value of the leased object may be adjusted from the first value to the second value according to the credit score of the first user, the credit distribution of the second user, the user attribute of the first user, and the object attribute of the leased object.
  • the credit distribution of the second user can be used to represent the overall credit level of the second user, thereby indicating the credit level of the social relationship of the first user, and to some extent, the credit level of the first user. Therefore, the credit distribution of the second user and the credit score of the first user are used to comprehensively reflect the credit level of the first user, and the effect is more accurate and reliable from a macroscopic and statistical perspective.
  • the credit score of the first user of the history, the credit distribution of the second user of the history, the attribute information of the first user of the history, the attribute information of the historical lease object, and the attribute value of the historical lease object is trained by a machine learning method to obtain a function model for adjusting the attribute value of the rental object.
  • the machine learning method can adopt Logistic Regression, Support Vector Machine (SVM), decision tree and other methods; the main processing flow of the above machine learning method is: numerical representation of sample features, feature data preprocessing, construction Machine learning model.
  • the initial first value is input as an input, and the function value of the leased object is determined by importing into the function model, that is, the function model The output - the second value.
  • the credit of the first user is divided into C
  • U i is the user attribute of the first user (such as gender, age, occupation, etc.)
  • D is the object attribute of the lease object (such as leasing) Object type, description, etc.
  • HRT is the initial attribute value of the leased object history
  • the m second users who are in a friend relationship with the first user are determined by using the method of FIG. 8. After determining the credit distributions L of the m second users, all the friends of the first user may also be determined.
  • User's credit distribution (the principle of determining the credit distribution of the user is the same as described above), so that according to the credit score of the first user, the credit distribution of the m second users determined, all the friend users of the first user The credit distribution is adjusted to adjust the attribute value of the lease object.
  • the credit threshold may also be set to calculate the second value. After determining the credit score of the first user and the credit score of the second user, the credit score of the first user is integrated with the credit of the second user (eg, adding or multiplying, and the specific algorithm can visually set the credit score
  • the threshold value is selected according to the method, and a comprehensive credit score is obtained; the ratio of the credit threshold value to the comprehensive credit score is multiplied by the initial value of the lease object to determine the second value after the lease object is adjusted;
  • the credit threshold is used to indicate the threshold value of the credit score.
  • the specific value can be set according to the actual situation; when the comprehensive credit score of the first user and the second user is higher than the set credit threshold, If the ratio of the credit threshold to the comprehensive credit score is less than 1, the ratio is multiplied by the initial value of the lease object to obtain a second value lower than the first value, and the credit score of the first user and the second user is achieved. High, the lower the attribute value of the leased object is adjusted; on the contrary, if the comprehensive credit score of the first user and the second user is lower than the set credit threshold, the ratio of the credit threshold to the comprehensive credit is set. If it is greater than 1, the second value after the rental object is adjusted will increase.
  • the method for adjusting the attribute value of the rental object provided by the embodiment of the present invention can be applied to the rental platform.
  • the application of the embodiment of the present invention can make the rent of the house adaptively adjust according to the credit of the tenant and the credit of the friend; For high tenants, rents can be reduced, attracting tenants to rent, and for tenants with low credit, rent can be increased, thereby reducing the risk of the lessor.
  • a specific implementation effect diagram of the tenant browsing the rental page of the house by using the renting platform is given.
  • the server can pass the relational database of the SNS platform.
  • Excavating the close friends of the tenant friends whose intimacy meets the intimacy conditions, or the m most intimate friends of the k communities from the tenant, and all the friends of the tenant;
  • the server can retrieve the credit score of the tenant through the credit information database of the SNS platform, the credit score of the tenant's close friend, and the credit score of all the tenants' tenants;
  • the server may determine the credit distribution of the tenant's close friends and the credit distribution of all the tenants' tenants;
  • the server can retrieve the historical rent of the house from the house rent database
  • the server will assign the tenant's identity attributes (gender, age, education, occupation, etc.), the house's house attributes (location, decoration, floor, etc.), the tenant's credit score, the tenant's close friend's credit distribution, and the tenant's
  • the credit distribution of all friends and the historical rental price of the house are imported into the pre-trained model for adjusting the rental price of the house to determine the rent
  • the adjusted house rental price in this model, the ratio of the historical rental price of the house to the adjusted rental price of the house is positively related to the credit score of the tenant and his friend; that is, the credit of the tenant and his friend The higher the rental price of the house is adjusted, the lower the credit of the tenant and its friends, and the higher the rental price after the house is adjusted;
  • the adjusted house rental price of the corresponding rental house page is fed back to the tenant.
  • the embodiment of the invention provides a method for adjusting the attribute value of the rental object, and solves the biggest problem in the rental of the house: the problem of trust, on the one hand, the adjustment of the rental price of the house based on the credit of the user and its friends, so that the rental price of the house is more accurate, and the lessor is enlarged. The proceeds. On the other hand, due to the more reasonable pricing brought by high credit, users are more inclined to increase the credit level, and the user atmosphere tends to be virtuous.
  • adjusting the rental price of the house based on the credit of the user and the friend is only one application of the rental platform in the embodiment of the present invention.
  • the embodiment of the present invention can also be applied to other needs to adjust the attribute value of the rental object according to different user situations.
  • the scenario enables flexible and intelligent adjustment of the attribute values of the leased object.
  • the attribute value adjustment apparatus of the rental object provided by the embodiment of the present invention is described below.
  • the attribute value adjustment apparatus of the rental object described below can be referred to the corresponding reference object attribute value adjustment method described above.
  • the attribute value adjustment device of the lease object described below can be considered as a function module architecture required for the server to implement the lease object attribute value adjustment method provided by the embodiment of the present invention.
  • FIG. 11 is a structural block diagram of a rental object attribute value adjusting apparatus according to an embodiment of the present invention.
  • the apparatus is applicable to a server. Referring to FIG. 11, the apparatus includes:
  • the request acquisition module 100 is configured to acquire a lease object browsing request sent by the client, and the lease object browsing request is used to request information of at least one lease object on the first application platform;
  • the second user determining module 200 is configured to determine, according to the account of the first user in the second application platform, a second user that is in a friend relationship with the first user on the second application platform;
  • the credit score obtaining module 300 is configured to obtain, according to the account of the first user and the second user in the second application platform, the credit scores of the first user and the second user in the second application platform;
  • the attribute value adjustment module 400 is configured to adjust the attribute value of the lease object from the first value to the second value according to the credit score of the first user and the credit score of the second user; wherein, the first value of the lease object is from the first value Retrieving from an attribute value database of an application platform;
  • the attribute value feedback module 500 is configured to feed back the rental object browsing page to the client, where the attribute value of the rental object is in the rented object browsing page is the second value.
  • the ratio of the first value to the second value is positively correlated with the credit score of the first user and the credit share of the second user.
  • the second user determining module 200 includes:
  • a relationship chain obtaining sub-module configured to acquire a relationship chain of the first user in the second application platform according to the account of the first user in the second application platform; wherein the first user logs in the first account with the account in the second application platform Application platform
  • the second user determining submodule is configured to determine, according to the relationship chain, a second user that is in a friend relationship with the first user on the second application platform.
  • the second user determining module 200 is configured to determine, according to the relationship chain, a second user that is in a friend relationship with the first user in the second application platform, and specifically includes:
  • the second user determining module 200 is configured to determine a candidate friend user that is a direct friend relationship with the first user according to the relationship chain, and specifically includes:
  • a candidate friend user who is a direct friend relationship with the first user is determined.
  • the second user determining module 200 is configured to obtain historical interaction data of the first user and each candidate friend user in the second application platform according to the account of the first user in the second application platform, which specifically includes:
  • the second user determining module 200 is configured to determine, according to historical interaction data of the first user and each candidate friend user, the intimacy of the first user and each candidate friend user, including:
  • the intimacy of the first user and each candidate friend user in each selected community is determined according to historical interaction data of the first user and each candidate friend user in each selected community.
  • the second user determining module 200 is configured to: select, from the candidate friend users, the second user whose intimacy meets the set intimacy condition, specifically:
  • At least one candidate friend user having the highest affinity with the first user is selected to obtain m second users, where m is greater than k.
  • the second user determining module 200 is configured to select, from the selected communities, at least one candidate friend user that has the highest affinity with the first user, and obtain m second users, including:
  • the candidate friend users with the highest intimacy with the first user are respectively selected.
  • the attribute value adjustment module 400 is configured to adjust the attribute value of the leased object from the first value to the second value according to the credit score of the first user and the credit score of the second user, which specifically includes:
  • the attribute value of the leased object is adjusted from the first value to the second value according to the credit score of the first user, the credit distribution of the second user, the user attribute of the first user, and the object attribute of the leased object.
  • the attribute value adjustment module 400 is configured to: The attribute value of the leased object is adjusted from the first value to the second value according to the credit score of the first user and the credit score of the second user, and specifically includes:
  • the attribute value of the leased object is determined according to the credit score of the first user, the credit distribution of the m second users, the credit distribution of all the buddy users of the first user, the user attribute of the first user, and the object attribute of the leased object.
  • the first value is adjusted to the second value.
  • the attribute value adjustment module 400 can also perform the attribute value adjustment of the leased object in the following manner.
  • the ratio of the set credit threshold to the comprehensive credit is multiplied by the initial value of the lease object to determine the second value after the lease object is adjusted.
  • the server determines a second user who is in a friend relationship with the first user on the second application platform;
  • the second user adjusts the attribute value of the lease object in the credit score of the second application platform, and feeds back to the client the attribute value of the corresponding lease object is the second value. Therefore, the present invention adopts the credit score of the first user and the credit score of the second user who is a friend relationship with the first user to comprehensively reflect the credit level of the first user, and the obtained comprehensive credit level of the first user can be further improved. Fully and authoritatively characterizing the credit status of the first user. Therefore, according to the credit score of the first user and the credit score of the second user, the attribute value of the lease object is adjusted, and the attribute value of the lease object is more targeted. Smart adjustment.
  • an embodiment of the present invention further provides a server, where the server may include the foregoing lease object attribute value adjusting apparatus.
  • the hardware structure of the server may include: a processor 1, a communication interface 2, a memory 3, and a communication bus 4; wherein the processor 1, the communication interface 2, and the memory 3 complete communication with each other through the communication bus 4;
  • the communication interface 2 may be an interface of the communication module, such as an interface of the GSM module;
  • the processor 1 may be a central processing unit CPU, or an application specific integrated circuit (ASIC), or configured to One or more integrated circuits embodying embodiments of the present invention;
  • memory 3 may include high speed RAM memory, and may also include non-volatile memory, such as at least one disk memory.
  • the processor 1 is specifically configured to: obtain a lease object browsing request sent by the client; and the lease object browsing request is used to request information of at least one lease object on the first application platform;
  • the rental object browsing page is fed back to the client, and the attribute value indicating the rental object in the rental object browsing page is the second value.
  • An embodiment of the present invention further provides a lease object attribute value adjustment device, where the device includes:
  • a memory for storing program code and transmitting the program code to the processor
  • a processor configured to execute the foregoing lease object attribute value adjustment method according to the instruction in the program code.
  • the embodiment of the invention further provides a storage medium for storing program code, and the program code is used to execute the lease object attribute value adjustment method.
  • the embodiment of the invention further provides a computer program product comprising instructions, which, when run on a computer, causes the computer to perform the above-mentioned rental object attribute value adjustment method.
  • the embodiment of the present invention further provides a method for adjusting a leased object attribute value, which is applied to a server, and the method includes:
  • the server acquires a lease object browsing request sent by the client, and the lease object browsing request is used to request information of at least one lease object on the first application platform;
  • the server obtains credit scores of the first user and the second user in the second application platform according to the account of the first user and the second user in the second application platform;
  • the server adjusts the attribute value of the lease object from the first value to the second value according to the credit score of the first user and the credit score of the second user; wherein the first value of the lease object is from the attribute value database of the first application platform Medium transfer
  • the server feeds back the lease object browsing page to the client, and the attribute value indicating the lease object in the lease object browsing page is the second value.
  • the ratio of the first value to the second value is positively correlated with the credit score of the first user and the credit of the second user.
  • the server obtains a relationship chain of the first user in the second application platform according to the account of the first user in the second application platform, where the first user logs in to the account in the second application platform.
  • the server determines, according to the relationship chain, a second user who is a friend relationship with the first user on the second application platform.
  • the server determines, according to the relationship chain, the second user that is in a friend relationship with the first user on the second application platform, including:
  • the server determines, according to the relationship chain, a candidate friend user who is a direct friend relationship with the first user;
  • the server obtains historical interaction data of the first user and each candidate friend user on the second application platform according to the account of the first user on the second application platform;
  • the server determines, according to historical interaction data of the first user and each candidate friend user, the intimacy of the first user and each candidate friend user;
  • the server selects, from each candidate friend user, a second user whose intimacy meets the set intimacy condition.
  • the server determines, according to the relationship chain, a candidate friend user that is a direct friend relationship with the first user, including:
  • the server obtains the community information of the first user in the second application according to the account of the first user in the second application platform, and selects k communities from the community of the first user;
  • the server determines, according to the relationship chain, a candidate friend user who is a direct friend relationship with the first user from the selected communities;
  • the server obtains historical interaction data of the first user and each candidate friend user on the second application platform according to the account of the first user on the second application platform, including:
  • the server acquires historical interaction data of the first user and each candidate friend user in each selected community according to the account of the first user in the second application platform;
  • the server determines, according to historical interaction data of the first user and each candidate friend user, the intimacy of the first user and each candidate friend user, including:
  • the server determines, according to historical interaction data of the first user and each candidate friend user in each selected community, the intimacy of the first user and each candidate friend user in each selected community;
  • the server selects, from among the candidate friend users, the second user whose intimacy meets the set intimacy condition includes:
  • the server selects at least one candidate friend user with the highest affinity from the first user from the selected communities, and obtains m second users, where m is greater than k.
  • the server selects at least one candidate friend user with the highest affinity from the first user from the selected communities, and obtains m second users including:
  • the server selects the first m-k+1 candidate friend users with the highest intimacy with the first user from the community in which the candidate user with the highest affinity of the first user is located;
  • the server selects the candidate friend users with the highest affinity from the first user from the remaining k-1 communities.
  • the server adjusts the attribute value of the leased object from the first value to the second value according to the credit score of the first user and the credit score of the second user, including:
  • the server divides the value range of the credit score into intervals, and determines a plurality of distribution intervals of the credit points;
  • the server determines, according to the credit score of each second user, a distribution interval of the credit points of each second user's credit branch, and obtains a credit distribution of the second user;
  • the server determines, according to the credit score of the first user, the credit distribution of the second user, the user attribute of the first user, and the object attribute of the leased object, the attribute value of the leased object is a second value, and the attribute value of the leased object is determined by the first A value is adjusted to a second value.
  • the server adjusts the attribute value of the leased object from the first value to the second value according to the credit score of the first user and the credit score of the second user, including:
  • the server determines a credit distribution of the m second users, and a credit distribution of all the friend users of the first user;
  • the server sets the attribute value of the leased object according to the credit score of the first user, the credit distribution of the m second users, the credit distribution of all the friend users of the first user, the user attribute of the first user, and the object attribute of the leased object. Adjusted from the first value to the second value.
  • the server adjusts the attribute value of the leased object from the first value to the second value according to the credit score of the first user and the credit score of the second user, including:
  • the server integrates the credit score of the first user with the credit score of the second user to obtain a comprehensive credit score
  • the server sets the ratio of the credit threshold to the comprehensive credit, multiplies the first value of the lease object, and determines the second value of the lease object.
  • the steps of a method or algorithm described in connection with the embodiments disclosed herein can be implemented directly in hardware, a software module executed by a processor, or a combination of both.
  • the software module can be placed in random access memory (RAM), memory, read only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or technical field. Any other form of storage medium known.

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Abstract

本发明提供了租赁对象属性值调整方法、装置及服务器,该方法包括:获取客户端发送的租赁对象浏览请求;根据第一用户在第二应用平台的账号,确定与第一用户在第二应用平台为好友关系的第二用户;获取第一用户的信用分及第二用户的信用分;根据第一用户的信用分,及第二用户的信用分,将租赁对象的属性值由第一值调整为第二值;向客户端反馈租赁对象的属性值为第二值。本发明实施例可提升租赁对象属性值调整的灵活性和智能性。

Description

租赁对象属性值调整方法、装置及服务器
本申请要求于2016年11月18日提交中国专利局、申请号为201611019016.2、申请名称为“共享租赁平台的租赁对象属性值调整方法、装置及服务器”的中国专利申请的优先权,其全部内容通过引用结合在本申请中。
技术领域
本申请涉及数据处理技术领域,具体涉及租赁对象属性值的调整。
背景技术
租车、租房等租赁平台的兴起,为用户在生活、工作的各方面提供了便利。用户可在租赁平台上浏览房屋、车辆等租赁对象的信息,并决定是否租赁租赁平台上的某一租赁对象。
当用户有租赁需求时,可以在租赁平台上浏览租赁对象的信息,用户在租赁对象的信息中较为关注的是租赁对象的属性值,通过浏览租赁对象的属性值,决定是否租下该租赁对象。例如,用户可在租房平台上,浏览房屋出租信息,并重点关注出租价格(即出租房屋的属性值),在房屋的出租价格符合预期时,才决定租下该房屋。
而对于租赁平台而言,其租赁对象的属性值一般是根据需求差异进行定价的,即,通常考虑市场供需关系而设定相应的属性值,例如,在租房平台或度假型酒店的房屋预订平台上,周六日的出租价格比工作日要高,显然,这种租赁对象的属性值调整方式不够灵活。
发明内容
有鉴于此,本发明实施例提供了一种租赁对象属性值调整方法、装置及服务器,以提升租赁平台中租赁对象的属性值调整的灵活性和智能性。
在本发明第一方面提供了一种租赁对象属性值调整方法,包括:
获取客户端发送的租赁对象浏览请求;租赁对象浏览请求,用于请求第一应用平台上的至少一个租赁对象的信息;
根据第一用户在第二应用平台的账号,确定与第一用户在第二应用平台为好友关系的第二用户;
根据第一用户和第二用户在第二应用平台的账号,分别获取第一用户及第二用户在第二应用平台的信用分;
根据第一用户的信用分,及第二用户的信用分,将租赁对象的属性值由第一值调整为第二值;其中,租赁对象的第一值从第一应用平台的属性值数据库中调取;
向所述客户端反馈租赁对象浏览页面,所述租赁对象浏览页面中指示所述租赁对象的属性值为所述第二值。
上述租赁对象属性值调整方法,通过获取第一用户在第二应用平台的好友用户,作为第二用户,以第一用户的信用分结合第二用户的信用分,来对第一用户浏览的租赁对象的属性值进行调整,第一用户的信用分以及第二用户的信用分,能够体现第一 用户的信用程度,从而能够实现根据租户的信用程度,灵活、智能地调整租赁对象的属性值。
其中,确定与第一用户在第二应用平台为好友关系的第二用户包括:
根据第一用户在第二应用平台的账号,获取第一用户在第二应用平台的关系链;其中,第一用户以在第二应用平台的账号,登录第一应用平台;
根据关系链,确定与第一用户在第二应用平台为好友关系的第二用户。
在一种可能的实现方式下,第一值与第二值的比值,与第一用户的信用分及第二用户的信用分为正相关关系。
在一种可能的实现方式下,根据关系链,确定与第一用户在第二应用平台为好友关系的第二用户包括:
根据关系链,确定与第一用户为直接好友关系的候选好友用户;
根据第一用户在第二应用平台的账号,获取第一用户与各候选好友用户在第二应用平台的历史互动数据;
根据第一用户与各候选好友用户的历史互动数据,确定第一用户与各候选好友用户的亲密度;
从各候选好友用户中,选取亲密度符合设定亲密度条件的第二用户。
上述租赁对象属性值调整方法中,第二用户为第一用户的亲密好友,与第一用户的社交关心更加紧密,能够更加贴切的体现第一用户的信用程度,那么,利用第一用户的亲密好友的信用分,以及第一用户的信用分,来综合表征第一用户的信用程度,会更加可靠。
在一种可能的实现方式下,根据关系链,确定与第一用户为直接好友关系的候选好友用户包括:
根据第一用户在第二应用平台的账号,获取第一用户在第二应用的社群信息,并从第一用户的社群中选取k个社群;
根据关系链,从所选取的各社群中,确定与第一用户为直接好友关系的候选好友用户;
根据第一用户在第二应用平台的账号,获取第一用户与各候选好友用户在第二应用平台的历史互动数据包括:
根据第一用户在第二应用平台的账号,获取第一用户与所选取的各社群中的各候选好友用户的历史互动数据;
根据第一用户与各候选好友用户的历史互动数据,确定第一用户与各候选好友用户的亲密度包括:
根据第一用户与所选取的各社群中的各候选好友用户的历史互动数据,确定第一用户与所选取的各社群中的各候选好友用户的亲密度;
从各候选好友用户中,选取亲密度符合设定亲密度条件的第二用户包括:
从所选取的各社群中,分别选取与第一用户的亲密度最高的至少一个候选好友用户, 得到m个第二用户,其中,m大于k。
在一种可能的实现方式下,从所选取的各社群中,分别选取与第一用户的亲密度最高的至少一个候选好友用户,得到m个第二用户包括:
从与第一用户的亲密度最高的候选好友用户所在的社群中,选取与第一用户的亲密度最高的前m-k+1个候选好友用户;
从剩余的k-1个社群中,分别选取与第一用户的亲密度最高的一个候选好友用户。
上述租赁对象属性值调整方法中,第二用户限定为从第一用户所在的社群中选取,选取不同的社群中的第二用户,得到与第一用户为不同社交关系的第二用户的信用分,用于综合体现第一用户在多中社群关系中的信用程度,表征的第一用户的信用程度更加准确。
在一种可能的实现方式下,根据第一用户的信用分,及第二用户的信用分,将租赁对象的属性值由第一值调整为第二值包括:
将信用分的取值范围划分区间,确定出信用分的多个分布区间;
根据各第二用户的信用分,确定各第二用户的信用分所处的信用分的分布区间,得到第二用户的信用分分布;
根据第一用户的信用分、第二用户的信用分分布、第一用户的用户属性、租赁对象的对象属性,将租赁对象的属性值由第一值调整为第二值。
在一种可能的实现方式下,根据第一用户的信用分,及第二用户的信用分,将租赁对象的属性值由第一值调整为第二值包括:
确定m个第二用户的信用分分布,及第一用户的所有好友用户的信用分分布;
根据第一用户的信用分、m个第二用户的信用分分布、第一用户的所有好友用户的信用分分布、第一用户的用户属性、租赁对象的对象属性,将租赁对象的属性值由第一值调整为第二值。
在一种可能的实现方式下,根据第一用户的信用分,及第二用户的信用分,将租赁对象的属性值由第一值调整为第二值包括:
将第一用户的信用分与第二用户的信用分相综合,得到综合信用分;
将设定信用分阈值与所示综合信用分的比值,乘以租赁对象的第一值,确定租赁对象的第二值。
上述租赁对象属性值调整方法中,基于第一用户的信用分和第二用户在第二应用平台的信用分分布,对租赁对象的属性值进行调整。显然,第二用户在第二应用平台的信用分分布,是经过大量数据来显示第二用户的信用程度,能够从更加宏观的角度表现第二用户的信用程度高低,再结合第一用户的信用分,能够更加智能地综合第一用户的信用程度。
在本发明第二方面提供了一种租赁对象属性值调整装置,包括:
请求获取模块,用于获取客户端发送的租赁对象浏览请求;租赁对象浏览请求,用于 请求第一应用平台上的至少一个租赁对象的信息;
第二用户确定模块,用于根据第一用户在第二应用平台的账号,确定与第一用户在第二应用平台为好友关系的第二用户;
信用分获取模块,用于根据第一用户和第二用户在第二应用平台的账号,分别获取第一用户及第二用户在第二应用平台的信用分;
属性值调整模块,用于根据第一用户的信用分,及第二用户的信用分,将租赁对象的属性值由第一值调整为第二值;其中,租赁对象的第一值从第一应用平台的属性值数据库中调取;
属性值反馈模块,用于向客户端反馈租赁对象浏览页面,租赁对象浏览页面中指示租赁对象的属性值为第二值。。
在一种可能的实现方式下,第二用户确定模块,包括:
关系链获取子模块,用于根据第一用户在第二应用平台的账号,获取第一用户在第二应用平台的关系链;其中,第一用户以在第二应用平台的账号,登录第一应用平台;
第二用户确定子模块,用于根据关系链,确定在第二应用平台中,与第一用户为好友关系的第二用户。
在一种可能的实现方式下,第一值与第二值的比值,与第一用户的信用分及第二用户的信用分成正相关关系。
在一种可能的实现方式下,第二用户确定子模块,用于根据关系链,确定与第一用户在第二应用平台为好友关系的第二用户,具体包括:
第一确定单元,用于根据关系链,确定与第一用户为直接好友关系的候选好友用户;
第一获取单元,用于根据第一用户在第二应用平台的账号,获取第一用户与各候选好友用户在第二应用平台的历史互动数据;
第二确定单元,用于根据第一用户与各候选好友用户的历史互动数据,确定第一用户与各候选好友用户的亲密度;
选取单元,用于从各候选好友用户中,选取亲密度符合设定亲密度条件的第二用户。
在一种可能的实现方式下,第一确定单元,包括:
第一获取子单元,用于根据第一用户在第二应用平台的账号,获取第一用户在第二应用的社群信息,并从第一用户的社群中选取k个社群;
第一确定子单元,用于根据关系链,从所选取的各社群中,确定与第一用户为直接好友关系的候选好友用户;
第一获取单元,包括:
第二获取子单元,用于根据第一用户在第二应用平台的账号,获取第一用户与所选取的各社群中的各候选好友用户的历史互动数据;
第二确定单元,包括:
第二确定子单元,用于根据第一用户与所选取的各社群中的各候选好友用户的历史互 动数据,确定第一用户与所选取的各社群中的各候选好友用户的亲密度;
选取单元,包括:
选取子单元,用于从所选取的各社群中,分别选取与第一用户的亲密度最高的至少一个候选好友用户,得到m个第二用户,其中,m大于k。
在一种可能的实现方式下,选取子单元,包括:
第一选取子单元,用于从与第一用户的亲密度最高的候选好友用户所在的社群中,选取与第一用户的亲密度最高的前m-k+1个候选好友用户;
第二选取子单元,用于从剩余的k-1个社群中,分别选取与第一用户的亲密度最高的一个候选好友用户。
在一种可能的实现方式下,属性值调整模块,用于根据第一用户的信用分,及第二用户的信用分,将租赁对象的属性值由第一值调整为第二值,具体包括:
将信用分的取值范围划分区间,确定出信用分的多个分布区间;
根据各第二用户的信用分,确定各第二用户的信用分所处的信用分的分布区间,得到第二用户的信用分分布;
根据第一用户的信用分、第二用户的信用分分布、第一用户的用户属性、租赁对象的对象属性,将租赁对象的属性值由第一值调整为第二值。
在一种可能的实现方式下,属性值调整模块,包括:
信用分确定子模块,用于确定m个第二用户的信用分分布,及第一用户的所有好友用户的信用分分布;
属性值调整子模块,用于根据第一用户的信用分、m个第二用户的信用分分布、第一用户的所有好友用户的信用分分布、第一用户的用户属性、租赁对象的对象属性,将租赁对象的属性值由第一值调整为第二值。
在一种可能的实现方式下,属性值调整模块,包括:
综合子模块,用于将第一用户的信用分与第二用户的信用分相综合,得到综合信用分;
计算子模块,用于将设定信用分阈值与所示综合信用分的比值,乘以租赁对象的第一值,确定租赁对象的第二值。
上述租赁对象属性值调整装置,与方法实施例对应,达到的效果也一致,这里不再赘述。
在本发明第三方面提供了一种服务器,包括上述租赁对象属性值调整装置。
在本发明的第四方面提供了一种租赁对象属性值调整方法,应用于服务器,该方法包括:
服务器获取客户端发送的租赁对象浏览请求;所述租赁对象浏览请求,用于请求第一应用平台上的至少一个租赁对象的信息;
服务器根据所述第一用户在第二应用平台的账号,确定与所述第一用户在所述第二应用平台为好友关系的第二用户;
服务器根据所述第一用户和所述第二用户在所述第二应用平台的账号,分别获取所述第一用户及所述第二用户在所述第二应用平台的信用分;
服务器根据所述第一用户的信用分,及所述第二用户的信用分,将所述租赁对象的属性值由第一值调整为第二值;其中,所述租赁对象的第一值从所述第一应用平台的属性值数据库中调取;
服务器向所述客户端反馈租赁对象浏览页面,所述租赁对象浏览页面中指示所述租赁对象的属性值为所述第二值。
在本发明第五方面还提供了一种租赁对象属性值调整设备,设备包括:
处理器以及存储器;
存储器,用于存储程序代码,并将程序代码传输给处理器;
处理器,用于根据程序代码中的指令执行上述租赁对象属性值调整方法。
在本发明第六方面还提供了一种存储介质,存储介质用于存储程序代码,程序代码用于执行上述租赁对象属性值调整方法。
在本发明第七方面还提供了一种包括指令的计算机程序产品,当其在计算机上运行时,使得计算机执行上述租赁对象属性值调整方法。
基于上述技术方案,本发明提供的租赁对象属性值调整方法中,服务器在获取到客户端发送的租赁对象浏览请求后,确定与第一用户在第二应用平台为好友关系的第二用户;从而基于第一用户和第二用户在第二应用平台的信用分,对租赁对象的属性值进行调整,并向客户端反馈相应的租赁对象的属性值为第二值。因此,本发明采用第一用户的信用分,及与该第一用户为好友关系的第二用户的信用分,来综合体现第一用户的信用程度,得到的第一用户的综合信用程度能够更加全面、权威地表征第一用户的信用状况,故,根据第一用户的信用分和第二用户的信用分,对租赁对象的属性值进行调整,实现灵活、智能地调整租赁对象的属性值。
附图说明
图1所示为根据本发明实施例的实现租赁对象属性值调整方法的系统结构示意图;
图2所示为根据本发明实施例的一种租赁对象属性值调整方法的信令流程图;
图3所示为根据本发明实施例的用户操作触发客户端发送租赁对象浏览请求的示意图;
图4所示为根据本发明实施例的租赁对象属性值调整方法的应用场景示意图;
图5所示为根据本发明实施例的租赁对象属性值调整方法的应用场景效果示意图;
图6所示为根据本发明实施例的确定第二用户的一种实现方法的流程图;
图7所示为根据本法明实施例的租赁对象属性值调整方法中用户的社群示意图;
图8所示为根据本发明实施例提供的确定第二用户的另一种实现方法的流程图;
图9所示为根据本发明实施例提供的调整租赁对象的属性值的方法流程图;
图10所示为根据本发明实施例的租赁对象属性值调整方法的另一应用场景示意图;
图11所示为根据本发明实施例的租赁对象属性值调整装置的结构框图;
图12所示为根据本发明实施例的服务器的硬件结构框图。
具体实施方式
下面将结合本发明实施例中的附图,对本发明实施例中的技术方案进行清楚、完整地描述,显然,所描述的实施例仅仅是本发明的一部分实施例,而不是全部的实施例。基于本发明中的实施例,本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例,都属于本发明保护的范围。
随着大众对于“共享”概念的逐渐接纳和需要,租赁市场变得日益火爆,尤其是租车、租房,给人们带来了很多便利。随之而来的是越来越多的租赁平台、租赁对象、租户,三者之间,存在着相互依赖和制约的关系,需要租赁对象的属性值(一般为价格)来平衡。当前存在的问题是:对于租赁平台而言,其租赁对象的属性值一般是根据需求差异进行定价的,调整定价的方式过于单一、不够灵活。例如,在租房平台上,周六、日的出租价格会比工作日高,显然,这种租赁对象的属性值调整方式不够灵活。
为了解决当前租赁平台遇到的上述问题,本申请实施例提供了一种租赁对象的属性值调整方法、装置及服务器,根据第一用户和第二用户在第二应用平台的信用分,对租赁对象的属性值进行调整,实现灵活、智能地调整租赁对象的属性值。
图1为本发明实施例提供的实现租赁对象属性值调整方法的系统架构图,参照图1,该系统架构可以包括:客户端10,服务器20,关系数据库30,属性值数据库40,征信数据库50。
其中,服务器20和属性值数据40属于第一应用平台;关系数据库30和征信数据库50属于第二应用平台;第一应用平台与第二应用平台为不同的应用平台,但第一应用平台可接入第二应用平台的账号,如用户可采用第二应用平台的账号,登录第一应用平台。当然,第一应用平台与第二应用平台还可以是相同的应用平台,第二应用平台能够提供第一应用平台所提供的租赁业务。
在具体实现时,第一应用平台可以是租房平台,第二应用平台可以是社会性网络服务(Social Networking Services,SNS)平台;用户可通过SNS平台的账号,登录租房平台;在具体实现时,也可通过SNS平台链接到租房平台。
在本发明实施例中,客户端10可以装载在智能手机、平板电脑、笔记本电脑等用户设备上,并与服务器20相通信。用户可通过客户端10访问服务器20,并请求浏览租赁对象。
在具体实现时,客户端10可以是单独开发的,与服务器20相配合的客户端;用户可以通过应用市场(APP STORE)或应用官方网站,将客户端下载到用户设备本地。客户端也可以是以浏览器的形式存在。
在具体实现时,客户端10也可能是第二应用平台的客户端,通过将第二应用平台的客户端界面嵌入链接第一应用平台的入口,可使得用户通过第二应用平台的客户端,与第一应用平台相链接,进入到第一应用平台对应的页面。
服务器20为第一应用平台所属服务器集群中的服务设备,架设在网络侧。在本发明实施例中,服务器20主要用于进行数据处理,根据不同的浏览租赁对象的用户,智能的调整 租赁对象的属性值。
关系数据库30为第二应用平台中记录各用户关系链的数据库,一个用户的关系链用于表示在第二应用平台上该用户与好友的关系对,通过关系数据库30可确定出各用户在第二应用平台的好友;在具体实现时,第二应用平台可以是SNS应用平台。
属性值数据库40为第一应用平台中记录各租赁对象属性值的数据库,比如,记录租赁对象的初始属性值。服务器20可在用户请求浏览租赁对象时,从属性值数据库40中获取租赁对象的初始属性值,并利用本发明实施例提供的方法,对租赁对象的初始属性值进行调整。
征信数据库50为第二应用平台中记录各用户的信用分的数据库。用户的信用分是根据用户历史时间段的金融、网络社交等的行为数据,度量出的用于表示用户信用程度的分值;用户的信用分预测用户在未来一段时间内按时还款的概率,或者债务违约的概率等。用户的信用分越高,则用户的信用程度越高。
用户的信用分可通过训练大量用户信用数据,得到预测用户信用的模型,将用户在金融、网络社交等行为数据导入到上述模型中,计算得到用户的信用分。
服务器20可通过征信数据库50的开放接口,获取到各用户的信用分;在具体实现时,征信数据库50可以是银行征信数据库、或者其他的开放查询用户的信用分的征信数据库,比如,具有大数据能力的SNS平台的征信数据库。
在本发明实施例中,服务器20可在租赁对象浏览页面中,为请求浏览租赁对象的不同用户展示租赁对象不同的属性值,达到为不同的用户提供租赁对象属性值区别化显示的目的;具体的,服务器20可根据当前请求浏览租赁对象的用户在第二应用平台的信用分、及该用户在第二应用平台的好友用户在第二应用平台的信用分,对租赁对象的属性值进行灵活、智能调整。
基于图1所示的系统结构示意图,下面对本发明实施例提供的租赁对象属性值调整方法进行介绍。
参见图2,图2为本发明实施例提供的租赁对象属性值调整方法的信令流程,该方法可以包括:
步骤S10,客户端向服务器发送租赁对象浏览请求。
在具体实现时,客户端可由第一用户操作。
客户端可基于第一用户的操作,向服务器发送租赁对象浏览请求;如客户端在检测到第一用户所触发的操作,请求进入租赁对象浏览页面的指令时,客户端向服务器发送租赁对象浏览请求。其中,租赁对象浏览页面是用于展示租赁对象的页面,如房屋出租页面,车辆出租页面等,该页面一般除了展示租赁对象,还必须展示该租赁对象的属性值。
以租房场景为例,如图3所示,用户在租房页面点击了一个房屋的出租信息后,触发客户端发送浏览所点击的房屋出租信息请求给服务器;相应的,服务器将在房屋出租页面,展示该房屋的位置、楼层、租金等信息,在这个过程中,服务器可应用本发明实施例提供的方法,调整显示的房屋租金。
步骤S11,服务器根据第一用户在第二应用平台的账号,获取第一用户在第二应用平台的关系链。
在具体实现时,第一应用平台可接入第二应用平台的账号,用户可通过第二应用平台的账号,登录第一应用平台。
相应的,在步骤S10执行之前,第一用户可向第一应用平台的服务器发送登录请求,具体可以是以第一用户在第二应用平台的账号,登录第一应用平台的请求;服务器在验证通过后,第一用户可以以其在第二应用平台的账号登录第一应用平台。例如,第一应用平台为租房平台,第二应用平台为微信平台时,用户可以利用其在微信平台的账号,直接登录租房平台。在具体实现时,第二应用平台上包含关系数据库,该关系数据库记录第二应用平台的各用户,在第二应用平台的关系链。第一应用平台的服务器,在确定第一用户在第二应用平台的账号后,可通过第二应用平台中关系数据库的开放接口,查询第一用户在第二应用平台的账号对应的关系链,得到第一用户在第二应用平台的关系链。
关系链用于记录第一用户在第二应用平台的关系对,可基于第一用户的关系链,确定出第一用户在第二应用平台的好友。在具体实现时,第一用户的关系链还可以记录与第一用户为好友关系的第二用户在第二应用平台的用户标识(如用户账号),即,关系链可以将各用户在第二应用平台的用户标识以用户间的关系相连接,形成表示用户间关系的链条。
步骤S12,服务器根据上述关系链,确定与第一用户在第二应用平台为好友关系的第二用户。
在具体实现时,第二用户可以是在第二应用平台与第一用户为好友关系的所有好友用户;也可以是从第一用户在第二应用平台的所有好友用户中,选取的与第一用户为亲密好友的用户。其中,所确定的第二用户的数量至少为一个。
当然,确定与第一用户在第二应用平台为好友关系的第二用户,除了采用上述步骤S11、S12中关系链的实现方式,还可以采用其他的实现方式,例如:在第一应用平台上,保存有第一用户的账号与第二用户的对应关系,其中,第二用户是第一用户在第二应用平台的好友用户。那么,第一用户可以直接在第一应用平台上,根据第一用户的账号查找与第一用户在第二应用平台为好友关系的用户——第二用户。
步骤S13,服务器根据第一用户和第二用户在第二应用平台的账号,分别获取第一用户及第二用户在第二应用平台的信用分。
在具体实现时,第二应用平台的征信数据库,用于记录第二应用平台的各用户在第二应用平台的信用分,一般情况下,该征信数据库中存储用户的账号与该用户的信用分的对应关系。服务器根据第一用户在第二应用平台的账号,通过第二应用平台征信数据库的开放接口,获取到第一用户在第二应用平台的信用分;服务器根据第二用户在第二应用平台的账号,通过第二应用平台征信数据库的开放接口,获取到第二用户在第二应用平台的信用分。
步骤S14,服务器根据第一用户的信用分,及第二用户的信用分,将租赁对象的属性值由第一值调整为第二值。
在具体实现时,第一值记录在第一应用平台的属性值数据库中,是租赁对象的初始属性值,该初始属性值是给该租赁对象预设的一个属性值。故,服务器可从第一应用平台的属性值数据库中获取租赁对象的初始属性值——第一值。
在确定第一用户在第二应用平台的信用分,及第二用户在第二应用平台的信用分后, 服务器可根据第一用户的信用分,及第二用户的信用分,利用预先建立的预测用户信用的模型,得到该第一用户对应的调整后属性值——第二值。因此,利用第二值对租赁对象的初始属性值进行调整,即,将租赁对象的属性值由第一值调整为第二值,实现由第一用户和第二用户的信用程度调整的租赁对象的属性值。
其中,,第一值与第二值的比值,与第一用户的信用分及第二用户的信用分为正相关关系;即,第一用户与第二用户的信用分越高,说明第一值与第二值的比值越大,则租赁对象调整后的第二值越小;第一用户与第二用户的信用分越低,说明第一值与第二值的比值越小,则租赁对象调整后的第二值越大。例如,租赁对象为出租的房屋、租赁对象的属性值为房屋的租金,对于同一个出租的房屋而言,其初始的租金——第一值是一个固定数值,则第一用户与第二用户的信用分越高,需要第一值和第二值的比值越大,那么调整后的房屋的租金——第二值作为分母,就越小;反之,第一用户与第二用户的信用分越低,需要第一值和第二值的比值越小,那么调整后的房屋的租金——第二值作为分母,就越大。可见,针对信用程度高的用户,展示较小的租赁对象的属性值,针对信用程度较低的用户,展示较大的租赁对象的属性值。
需要注意的是,本发明实施例并不仅通过浏览租赁对象的第一用户自身的信用分,对租赁对象的属性值进行调整,还考虑了与第一用户为好友关系的第二用户的信用分,通过将第一用户及第二用户的信用分相结合,使得对第一用户的信用程度的评估更为真实、准确;依据第一用户及第二用户的信用分,所调整的租赁对象的属性值,也将更为贴近第一用户的信用程度,租赁对象调整后的属性值与第一用户的信用程度也得到了更好的匹配。
通过向信用程度较高的用户,反馈较低的租赁对象的属性值,可以提高租赁对象的拥有者寻找到高信用的租客的可能性;反之,通过向信用程度较低的用户,反馈较高的租赁对象的属性值,可以为租赁对象的拥有者规避低信用租客,降低了租赁对象的拥有者在租赁过程中的风险。
步骤S15,服务器向客户端反馈租赁对象浏览页面,其中,该租赁对象浏览页面中指示租赁对象的属性值为第二值。
服务器在将租赁对象的属性值调整为第二值后,在向第一用户反馈的租赁对象浏览页面中,租赁对象的属性值为第二值,使第一用户可以对租赁对象的属性信息进行针对性的浏览。当然,还可以采用其它方式向用户反馈租赁对象的第二值,这里不再赘述。
本发明实施例提供的租赁对象属性值的调整方法中,服务器在获取到客户端发送的租赁对象浏览请求后,可确定第一用户在第二应用平台的关系链,基于该关系链,确定出在第二应用平台上与第一用户为好友关系的第二用户;从而基于第一用户和第二用户在第二应用平台的信用分,对上述租赁对象的属性值进行调整,得到属性值为第二值的租赁对象,并向客户端反馈该调整后的租赁对象浏览页面;实现在用户浏览租赁对象时,基于用户及其好友的信用程度,向用户反馈灵活、智能调整租赁对象的属性值后的租赁对象浏览页面。本发明实施例基于浏览租赁对象的用户的信用分,及与该用户为好友关系的第二用户的信用分,用于综合的体现出该用户的信用程度,基于该用户的综合信用程度对租赁对象的属性值进行智能地调整,并向该用户反馈相应的租赁对象浏览页面,提升租赁对象浏览页面中租赁对象的属性值调整的灵活性和智能性。
在具体实现时,本发明实施例提供的租赁对象属性值调整方法,可应用于房屋出租价格的调整,在用户浏览房屋出租页面时,根据用户及其好友的信用分,对房屋的出租价格进行调整。
相应的,图4示出了本发明实施例提供的租赁对象属性值调整方法,在租房平台的应用示意图;包括:
第一用户通过客户端,使用SNS平台的账号登录租房平台;
第一用户通过客户端登录租房平台后,第一用户使用客户端请求房屋出租页面时,客户端向服务器发送房屋出租页面请求;
服务器接收房屋出租页面请求后,可确定租房平台上当前正在出租的房屋,并从租房平台的数据库中获取房屋的历史租金;
同时,服务器可利用第一用户在SNS平台的账号,从SNS平台的关系数据库中,查询到第一用户在SNS平台的关系链;
服务器根据该关系链,可确定出在SNS平台与第一用户为好友关系的第二用户,并从关系链中确定出第二用户在SNS平台的账号;
服务器从SNS平台的征信数据库中,调取到第一用户的信用分及第二用户的信用分;
服务器根据第一用户的信用分及第二用户的信用分,对各房屋的历史租金进行调整;其中,各房屋的历史租金与调整后租金的比值,与第一用户的信用分及第二用户的信用分为正相关关系;即,在房屋的历史租金为某一固定值时,第一用户及第二用户的信用分越高,调整后的房屋租金越低,第一用户及第二用户的信用分越低,调整后的房屋租金越高;
服务器将调整房屋租金后的房屋出租页面反馈给客户端。
针对图4所示的应用场景,利用本发明实施例提供的租赁对象属性值调整方法,得到图5所示的应用效果图,当用户在浏览房屋出租页面时,如图5所示,客户端上显示的内容为:房屋的历史租金(图5所示的原租金),及结合第一用户及其好友用户的信用分调整后的租金(图5所示的信用优惠租金)。可见,在第一用户及其好友用户的信用程度较高的情况下,房屋调整后的租金有所下降。
本发明实施例提供的租赁对象属性值调整方法,也可以应用于其他的租房、租车等闲置物品的租赁场景中。具体的,基于用户及其好友的信用分,综合的体现该用户的信用程度,基于该用户的综合信用程度,灵活、智能地调整租赁对象的属性值,对信用高的用户,房屋、车辆等闲置物品的租金可以降低,吸引该信用高的用户,并且使得出租方能够找到满意的租客;而对信用低的用户,可以提高租金,降低出租方的出租风险,使得房屋、车辆等闲置物品能够得到合理的利用。
在另一种实现方式中,本发明实施例在利用用户的好友用户的信用分,调整租赁对象的属性值时,选择利用用户的亲密好友的信用分;相应的,图1所示步骤S12在确定与第一用户为好友关系的第二用户时,可以确定第一用户的亲密好友为第二用户。
在具体实现时,图6示出了确定与第一用户为亲密好友关系的第二用户的方法流程图,该方法可应用于服务器,参照图6,该方法包括:
步骤S20,服务器根据关系链,确定与第一用户为直接好友关系的候选好友用户。
第一用户的关系链,指示了与第一用户为好友关系的好友用户;而关系链中好友用户与第一用户的关系,可以通过“度”来衡量;度(degree)指的是关系链的连接图中的连接关系,一度好友认为是直接好友,二度好友认为是好友的好友,以此类推。本发明实施例从第一用户的关系链中,确定与第一用户为一度好友的好友用户,即,第一用户的直接好友,并将所确定的好友用户作为候选好友用户。
步骤S21,服务器根据第一用户在第二应用平台的账号,获取第一用户与各候选好友用户在第二应用平台的历史互动数据。
步骤S22,服务器根据上述第一用户与各候选好友用户的历史互动数据,确定第一用户与各候选好友用户之间的亲密度。
在具体实现时,第一用户与候选好友用户的亲密度,可通过第一用户与候选好友用户在设定历史时间段内的互动次数确定,第一用户与候选好友用户在设定历史时间段内的互动次数越多,则第一用户与候选好友用户的亲密度越高;即第一用户与候选好友用户在设定历史时间段内的互动次数,与第一用户与候选好友用户的亲密度成正相关关系。
在具体实现时,第一用户与一候选好友用户的互动次数可以包括:第一用户接收候选好友用户单聊消息的次数,第一用户向候选好友用户发送单聊消息的次数,候选好友用户在朋友圈评论第一用户发表的内容的次数,第一用户与候选好友用户在朋友圈互相评论的次数等之中的至少一个。
在具体实现时,服务器可通过第一用户在第二应用平台的账号,从第二应用平台的数据库中,获取到第一用户与候选好友用户的互动次数。
在一种实现方式中,可以通过机器学习的方法,根据用户与好友用户的互动次数,计算用户与各位候选好友用户的亲密度,学习到相应的数学模型;根据第一用户与各候选好友用户的互动次数,通过构建的数学模型,计算出第一用户与各候选好友的亲密度。
若设第一用户为U,第一用户的一候选好友用户为M,R为第一用户U收取候选好友用户M单聊消息的次数,S为第一用户U向候选好友用户M发送单聊消息的次数,CR为候选好友用户M在朋友圈评论第一用户U发表的内容的次数,CS为第一用户U与候选好友用户M在朋友圈互相评论的次数;则通过构建的模型对应的函数F,计算第一用户U与候选好友用户M的亲密度Q的公式可以如下:
Q=F(R,S,CR,CS)。
例如,Q=F=1/(1+e-1*(-0.3*R+0.15*S-0.4*CR-0.1*CS))
在具体实现时,如果确定第一用户候选好友的数量为5个,分别为M1,M2,M3,M4和M5,则下表1示出了第一用户分别与该5个候选好友的亲密度。
表1第一用户与候选好友的亲密度
Figure PCTCN2017107300-appb-000001
步骤S23,服务器从候选好友用户中,选取亲密度符合设定亲密度条件的第二用户。
步骤S23所选取的第二用户,与图2所示的本发明实施例中,步骤S12所确定的与第一用户在第二应用平台为好友关系的第二用户,是确定第二用户的两种具体实现方式。显然,步骤S12所确定的第二用户,并不限于与第一用户的亲密度符合设定亲密度条件的好友用户,而是与第一用户为好友关系的所有好友用户。
例如,亲密度符合设定亲密度条件的第二用户是,候选好友用户中亲密度最大的m个好友用户(m为设定值);在具体实现时,可按照亲密度从大到小的顺序,对候选好友用户进行排序,选取出排序在前m位的好友用户,作为第二用户。
相应的,图2所示步骤S13和步骤S14可根据步骤S23所选取的第二用户实现。
另外,用户的社交关系中还可能存在社群关系,即社交网络中存在分群,相同的社群表示的第一用户U与社群内好友的结交方式相同,则该社群中用户的聚集系数较高;如图7所示,对于第一用户U,第一用户U的直接好友(一度好友)可以划分为三个社群,社群的类型通常表示第一用户U与社群内好友的结交方式;例如,社群A可能是第一用户U的同事社群,其中,A1、A2为第一用户U的一度好友(直接好友),A3为第一用户U的二度好友(好友的好友);社群B可能是第一用户U的亲友社群,其中,B1、B2为第一用户U的一度好友;社群C可能是第一用户U的同学社群,其中,C1为第一用户U的一度好友,C2为第一用户U的二度好友(好友的好友)。
由于不同的社群,对第一用户可能会存在不同程度的影响,因此在确定与第一用户为好友关系的第二用户时,除考虑与第一用户的亲密度外,还可以考虑第二用户所在的社群,从而使得所确定的第二用户能够覆盖到第一用户的不同社群。
在另一种可选的实现方式中,参见图8,给出了确定与第一用户为好友关系的第二用户的另一可选方法,该方法可应用于服务器,包括:
步骤S30,服务器根据第一用户在第二应用平台的账号,获取第一用户在第二应用的社群信息,并选取第一用户的k个社群。
其中,k为设定的社群数,可以是第一用户的所有社群,也可以是第一用户的部分社群。
当第一用户所拥有的社群数量较多时,可以预先设定社群类型和社群数,从第一用户的社群中选取出至少一个社群类型与设定社群类型相应的社群,并从剩余的社群中随机选取剩余数量的社群。其中,设定社群类型可以是与第一用户的关系紧密的社群类型,例如亲友社群、同学社群等;而第一用户由于兴趣爱好组成的社群,与第一用户的关系紧密度,显然低于第一用户的亲友社群、同学社群。
步骤S31,服务器根据第一用户的关系链,从所选取的各社群中,确定与第一用户为直接好友关系的候选好友用户。
在具体实现时,可从第一用户的k个社群的各社群中,确定与第一用户为一度好友的好友用户。
显然,步骤S30和步骤S31是图6所示的本发明实施例中步骤S20,在社群场景下的一种实现方式。
步骤S32,服务器根据第一用户在第二应用平台的账号,获取该第一用户与所选取的各社群中的各候选好友用户的历史互动数据。
显然,步骤S32是图6所示的本发明实施例中步骤S21,在社群场景下的一种实现方式。
步骤S33,服务器根据第一用户与所选取的各社群中的各候选好友用户的历史互动数据,确定第一用户与所选取的各社群中的各候选好友用户的亲密度。
显然,步骤S33是图6所示的本发明实施例中步骤S22,在社群场景下的一种实现方式。
步骤S34,服务器从选取的各社群中,分别选取与第一用户的亲密度最高的至少一个候选好友用户,得到与第一用户为好友关系的m个第二用户。
其中,m大于等于k。
显然,步骤S34是图6所示的本发明实施例中步骤S23,在社群场景下的一种实现方式。
在具体实现时,需从所确定的k个社群的各社群中,分别选取至少一个与第一用户的亲密度最高的候选好友用户,组成m个第二用户;即需从k个社群的各社群中均选择候选好友用户作为第二用户,构成m个第二用户,各社群选择的第二用户的数量可以是至少一个。
从所确定的k个社群的每个社群中选取第二用户,构成与第一用户为好友关系的m个第二用户的方式有多种;
一种选取方式为:从各社群中,分别选取相同数量的与第一用户的亲密度最高的候选好友用户,形成m个第二用户。即,每个社群中,将第一用户的候选好友用户按照与第一用户的亲密度从高到低进行排序;然后在每个社群中选取排在前(m/k)位的候选好友用户,作为第二用户,k个社群共选出m个候选好友用户,即为选取到的第二用户。
另一种选取方式为:从与第一用户的亲密度最高的候选好友用户所在的社群中选择多个与第一用户为候选好友关系的用户,再从剩余的其他社群中,平均的选取与第一用户的亲密度最高的候选好友用户。例如,每个社群中,仍然将第一用户的候选好友用户按照与第一用户的亲密度从高到低进行排序;从与第一用户的亲密度最高的候选好友用户所在的社群中,选取排在前a位的候选好友用户;再从剩余的k-1社群中,每个社群中选取排在前((m-a)/(k-1))位的候选好友用户,其中,a和((m-a)/(k-1))均为整数,其a大于((m-a)/(k-1));k个社群共选出m个候选好友用户,即为选取到的m个第二用户。
一种具体的选取方式为:在与第一用户的亲密度最高的候选好友用户所在的社群中,选取与第一用户的亲密度最高的前(m-k+1)个候选好友用户,再从剩余的(k-1)个社群中,分别选取与第一用户的亲密度最高的候选好友用户,得到与第一用户为好友关系的m个第二用户。
例如,设k为3,m为4时,如表2所示,已知第一用户的候选好友用户所在社群及亲密度,首先,需要确定A、B、C三个社群中与第一用户的亲密度最高的候选好友用户所在社群,最高的亲密度为0.9,对应的候选好友为A1、A2,他们归属于社群A;然后,从社群A中选取亲密度最高的、数量为:(m-k+1)=(4-3+1)=2的好友,作为第二用户,则 A社群中的A1、A2为第二用户;接着,从剩余的社群B、C中,选取亲密度最高的候选好友,为B1、C1,作为第二用户。即,从社群A、B和C中选取出与第一用户的亲密度最高的第二用户:A1、A2、B1,C1。
表2候选好友用户信息
候选好友用户 所在社群 与第一用户的亲密度 信用分
A1 A 0.9 730
A2 A 0.9 650
B1 B 0.7 600
B2 B 0.6 500
C1 C 0.5 340
通过图8所示的方法,确定出与第一用户为好友关系的m个第二用户后,可以利用图1所示的本发明实施例中步骤S12和步骤S13实现对租赁对象属性值的调整。
在具体实现时,在调整租赁对象的属性值时,本发明实施例可确定第二用户的信用分分布,结合第一用户的信用分和第二用户的信用分分布,调整租赁对象的属性值。
在具体实现时,参见图9,给出了根据第一用户的信用分及第二用户的信用分,调整租赁对象属性值的方法流程图,该方法可应用于服务器,包括:
步骤S40,将信用分的取值范围划分区间,确定出信用分的多个分布区间。
信用分的取值范围,由第二应用平台将信用分的最大值和最小值发送到第一应用平台,第一应用平台将该最大值和该最小值之间的取值范围作为信用分的取值范围。其中,第二应用平台获取信用分的最大值和最小值的具体实现方式,可以是第二应用平台统计该平台上的用户的信用分数据,得到信用分的最大值和最小值;还可以是,第二应用平台只统计得到信用分的最大值,最小值可以是第二应用平台预先设定;也可以是第二应用平台根据该平台上用户的情况,在第二应用平台预先设定信用分的最大值和最小值。当然,还可以采用其他方式,例如,第一应用平台从第二应用平台根据实际情况对信用分的取值范围进行预先设置,这里不再赘述。
在具体实现时,信用分的分布区间可以满足频数分布、正态分布等。
本发明实施例中,可设定每一个分布区间对应的信用分取值,从而将信用分的取值范围,按照各分布区间的信用分取值划分,得到信用分的多个分布区间。例如,信用分的取值范围为[300,900),每个分布区间的信用分取值为100,则可将信用分的取值范围的各个整百信用分除以100,得到如下表3所示的6个信用分的分布区间;其中,3的分布区间表示百位为3的信用分,4的分布区间表示百位为4的信用分,以此类推。
表3信用分的分布区间
分布区间 3 4 5 6 7 8
其中,表3中的3至8可以认为是信用分的取值范围的分箱(binning),分箱是指将连续变量离散化的一种常用手段,例如把0-99岁的人,进行分箱处理,可以分成0-18岁是未成年人,18-45是青年,45-60是中年,60以上是老年。
本发明实施例借助分箱手段,划分出信用分的取值范围对应的分箱,确定信用分的多个分布区间。显然,分箱不一定是通过将信用分的取值范围中的整百信用分除以100实现, 还可以是通过其他的分箱划分方法实现,在这里不作具体限定。
步骤S41,根据各第二用户的信用分,确定各第二用户的信用分所处于的信用分的分布区间,得到第二用户的信用分分布。
第二用户的信用分分布,可以表征第二用户的整体信用程度。如果第二用户的信用分分布大部分落在高信用分的分布区间,则说明第二用户的信用程度较高;反之,如果第二用户的信用分分布大部分落在低信用分的分布区间,则说明第二用户的信用程度较低。
以表2所示的与第一用户为好友关系的第二用户A1、A2、B1,C1的信用分为例,结合表3所示信用分的分布区间,第二用户的信用分分布可以如下表4所示。
表4第二用户的信用分分布
分布区间 3 4 5 6 7 8
用户数 1 0 0 2 1 0
如上文,确定第二用户的方式,可以是以图6所示方法确定的与第一用户的亲密度符合设定亲密度条件的第二用户;也可以是以图8所示方法确定的来自第一用户的k个社群的m个第二用户,还可以是以图2所示方法确定第一用户的所有直接好友用户为第二用户;等。
相应的,本发明实施例确定第二用户的信用分分布,可以是确定与第一用户的亲密度符合设定亲密度条件的第二用户的信用分分布,还可以是确定来自第一用户的k个社群的m个第二用户的信用分分布,也可以是确定第一用户的所有直接好友用户的信用分分布。
步骤S42,根据第一用户的信用分、第二用户的信用分分布、第一用户的用户属性、租赁对象的对象属性,将租赁对象的属性值由第一值调整为第二值。
在得到第二用户的信用分分布后,本发明实施例可根据第一用户的信用分、第二用户的信用分分布、第一用户的用户属性、租赁对象的对象属性、及租赁对象初始的第一值(初始属性值),调整租赁对象的属性值。即可根据第一用户的信用分、第二用户的信用分分布、第一用户的用户属性、租赁对象的对象属性,将租赁对象的属性值由第一值调整为第二值。
可见,第二用户的信用分分布,可以用于表征第二用户的整体信用程度,进而能够说明第一用户的社交关系的信用程度,一定程度上体现该第一用户的信用程度。故,利用第二用户的信用分分布和第一用户的信用分来综合体现第一用户的信用程度,从宏观和统计的角度,效果更加准确和可靠。
在具体实现时,将历史的第一用户的信用分、历史的第二用户的信用分分布、历史的第一用户的属性信息、历史的租赁对象的属性信息、及历史的租赁对象的属性值作为训练样本,以机器学习的方法,对上述训练样本进行训练,获得调整租赁对象的属性值的函数模型。其中,机器学习方法具体可以采用逻辑回归,支持向量机(Support Vector Machine,SVM),决策树等方法;上述机器学习方法的主要处理流程为:样本特征的数值化表示,特征数据预处理,构建机器学习模型。
在得到第二用户的信用分分布和第一用户的信用分后,将第一用户的信用分、第二用户的信用分分布、第一用户的用户属性、租赁对象的对象属性、及租赁对象的初始的第一值作为输入,导入该函数模型中,即可确定出租赁对象调整后的属性值,即,该函数模型 的输出——第二值。
如果设第二用户的信用分分布为L,第一用户的信用分为C,Ui为第一用户的用户属性(如性别、年龄、职业等),D为租赁对象的对象属性(如租赁对象的对象类型,描述等),HRT为租赁对象历史的初始属性值,则租赁对象调整后的属性值RT可以为RT=P(Ui,D,C,L,,HRT),其中P为训练得到的调整租赁对象的属性值的函数模型。
在具体实现时,以图8方法确定与第一用户为好友关系的m个第二用户,则在确定出该m个第二用户的信用分分布L后,还可确定第一用户的所有好友用户的信用分分布(用户的信用分分布的确定原理与上文描述相同),从而根据第一用户的信用分,所确定的m个第二用户的信用分分布,第一用户的所有好友用户的信用分分布,调整租赁对象的属性值。
例如,设第一用户的所有好友用户的信用分分布为L’,则租赁对象调整后的属性值RT为:RT=P(Ui,D,C,L,L’,HRT)。
在具体实现时,还可以设定信用分阈值,计算第二值。在确定出第一用户的信用分和第二用户的信用分后,将第一用户的信用分与第二用户的信用分相综合(如相加或相乘,具体算法可视设定信用分阈值的选取方式而定),得到综合信用分;将设定信用分阈值与综合信用分的比值,乘以租赁对象初始的第一值,确定出租赁对象调整后的第二值;
设定信用分阈值是用于表示信用分好坏的界限值,具体的取值可根据实际情况设定;当第一用户与第二用户的综合信用分高于设定信用分阈值时,设定信用分阈值与综合信用分的比值将小于1,则将该比值乘以租赁对象初始的第一值,得到第二值低于第一值,实现第一用户与第二用户的信用分越高,租赁对象调整后的属性值越低的目的;相反的,如果第一用户与第二用户的综合信用分,低于设定信用分阈值,则设定信用分阈值与综合信用分的比值将大于1,租赁对象调整后的第二值将增大。
本发明实施例提供的租赁对象属性值调整方法,可应用于租房平台,通过本发明实施例的运用,可使得房屋的租金根据租客的信用及其好友的信用进行适应性的调整;对信用高的租客,租金可以降低,吸引该租客租房,而对信用低的租客,可提高租金,从而降低出租方的风险。
如图10所示,给出了租客利用租房平台浏览房屋出租页面的具体的实现效果图,当某一租客向租房平台的服务器请求浏览房屋出租页面时,服务器可通过SNS平台的关系数据库,挖掘出该租客的亲密好友(亲密度符合设定亲密度条件的好友,或者,来自租客的k个社群的m个亲密度最高的好友等),及该租客的所有好友;
服务器可通过SNS平台的征信数据库调取到租客的信用分,租客的亲密好友的信用分,及租客的所有好友的信用分;
服务器可确定租客的亲密好友的信用分分布,及租客的所有好友的信用分分布;
服务器可从房屋租金数据库,调取到房屋的历史租金;
服务器将租客的身份属性(性别、年龄、学历、职业等)、房屋的房屋属性(位置,装饰、楼层等)、租客的信用分、租客的亲密好友的信用分分布、租客的所有好友的信用分分布、及房屋的历史出租价格,导入到预训练的调整房屋出租价格的模型中,确定出针对租 客调整后的房屋出租价格;在这个模型中,房屋的历史出租价格与房屋调整后的出租价格的比值,和租客及其好友的信用分,成正相关关系;即租客及其好友的信用越高,房屋调整后的出租价格越低,租客及其好友的信用越低,房屋调整后的出租价格越高;
服务器调整后的房屋出租价格相应的房屋出租页面,反馈给该租客。
本发明实施例提供租赁对象属性值调整方法,解决了房屋出租中最大的问题:信任问题,一方面,实现基于用户及其好友信用的房屋出租价格调整,使得房屋出租价格更加准确,扩大出租方的收益。另一方面,由于高信用带来的更合理的定价,使得用户更倾向于提高信用程度,使得用户氛围趋向于良性循环。
显然,基于用户及其好友信用调整房屋出租价格,仅是本发明实施例在租房平台的一个应用,本发明实施例还可应用在其他的需要根据不同的用户情况,调整租赁对象的属性值的场景,从而实现对租赁对象的属性值进行灵活、智能的调整。
下面对本发明实施例提供的租赁对象的属性值调整装置进行介绍,下文描述的租赁对象的属性值调整装置,可与上文描述的租赁对象属性值调整方法相互对应参照。下文描述的租赁对象的属性值调整装置可以认为是,服务器为实现本发明实施例提供的租赁对象属性值调整方法,所需设置的功能模块架构。
图11为本发明实施例提供的租赁对象属性值调整装置的结构框图,该装置可应用于服务器,参照图11,该装置包括:
请求获取模块100,用于获取客户端发送的租赁对象浏览请求;租赁对象浏览请求,用于请求第一应用平台上的至少一个租赁对象的信息;
第二用户确定模块200,用于根据第一用户在第二应用平台的账号,确定与第一用户在第二应用平台为好友关系的第二用户;
信用分获取模块300,用于根据第一用户和第二用户在第二应用平台的账号,分别获取第一用户及第二用户在第二应用平台的信用分;
属性值调整模块400,用于根据第一用户的信用分,及第二用户的信用分,将租赁对象的属性值由第一值调整为第二值;其中,租赁对象的第一值从第一应用平台的属性值数据库中调取;
属性值反馈模块500,用于向所述客户端反馈租赁对象浏览页面,所述租赁对象浏览页面中指示所述租赁对象的属性值为所述第二值。
在具体实现时,第一值与第二值的比值,与第一用户的信用分和第二用户的信用分成正相关关系。
其中,第二用户确定模块200,包括:
关系链获取子模块,用于根据第一用户在第二应用平台的账号,获取第一用户在第二应用平台的关系链;其中,第一用户以在第二应用平台的账号,登录第一应用平台;
第二用户确定子模块,用于根据关系链,确定与第一用户在第二应用平台为好友关系的第二用户。
在具体实现时,第二用户确定模块200,用于根据关系链,确定与第一用户在第二应用平台为好友关系的第二用户,具体包括:
根据关系链,确定与第一用户为直接好友关系的候选好友用户;
根据第一用户在第二应用平台的账号,获取第一用户与各候选好友用户在第二应用平台的历史互动数据;
根据第一用户与各候选好友用户的历史互动数据,确定第一用户与各候选好友用户的亲密度;
从候选好友用户中,选取亲密度符合设定亲密度条件的第二用户。
在具体实现时,第二用户确定模块200,用于根据关系链,确定与第一用户为直接好友关系的候选好友用户,具体包括:
根据第一用户在第二应用平台的账号,获取第一用户在第二应用的社群信息,并选取第一用户的k个社群;
根据关系链,从所选取的各社群中,确定与第一用户为直接好友关系的候选好友用户。
在具体实现时,第二用户确定模块200,用于根据第一用户在第二应用平台的账号,获取第一用户与各候选好友用户在第二应用平台的历史互动数据,具体包括:
根据第一用户在第二应用平台的账号,获取第一用户与所选取的各社群中的各候选好友用户的历史互动数据。
在具体实现时,第二用户确定模块200,用于根据第一用户与各候选好友用户的历史互动数据,确定第一用户与各候选好友用户的亲密度,具体包括:
根据第一用户与所选取的各社群中的各候选好友用户的历史互动数据,确定第一用户与所选取的各社群中的各候选好友用户的亲密度。
在具体实现时,第二用户确定模块200,用于从候选好友用户中,选取亲密度符合设定亲密度条件的第二用户,具体包括:
从所选取的各社群中,分别选取与第一用户的亲密度最高的至少一个候选好友用户,得到m个第二用户,其中,m大于k。
在具体实现时,第二用户确定模块200,用于从所选取的各社群中,分别选取与第一用户的亲密度最高的至少一个候选好友用户,得到m个第二用户,具体包括:
从与第一用户的亲密度最高的候选好友用户所在的社群中,选取与第一用户的亲密度最高的前m-k+1个候选好友用户;
从剩余的k-1个社群中,分别选取与第一用户的亲密度最高的候选好友用户。
在具体实现时,属性值调整模块400,用于根据第一用户的信用分,及第二用户的信用分,将租赁对象的属性值由第一值调整为第二值,具体包括:
将信用分的取值范围划分区间,确定出信用分的多个分布区间;
根据各第二用户的信用分,确定各第二用户的信用分所处于的信用分的分布区间,得到第二用户的信用分分布;
根据第一用户的信用分、第二用户的信用分分布、第一用户的用户属性、租赁对象的对象属性,将租赁对象的属性值由第一值调整为第二值。
在具体实现时,如果通过从第一用户的k个社群中,选取m个第二用户的方式,来确定与第一用户为好友关系的第二用户,则属性值调整模块400,用于根据第一用户的信用分,及第二用户的信用分,将租赁对象的属性值由第一值调整为第二值,具体包括:
确定m个第二用户的信用分分布,及第一用户的所有好友用户的信用分分布;
根据第一用户的信用分、m个第二用户的信用分分布、第一用户的所有好友用户的信用分分布、第一用户的用户属性、租赁对象的对象属性,将租赁对象的属性值由第一值调整为第二值。
属性值调整模块400还可采用如下方式进行租赁对象的属性值调整,
将第一用户的信用分与第二用户的信用分相综合,得到综合信用分;
将设定信用分阈值与综合信用分的比值,乘以租赁对象初始的第一值,确定租赁对象调整后的第二值。
本发明提供的租赁对象属性值调整装置中,服务器在获取到客户端发送的租赁对象浏览请求后,确定与第一用户在第二应用平台为好友关系的第二用户;从而基于第一用户和第二用户在第二应用平台的信用分,对租赁对象的属性值进行调整,并向客户端反馈相应的租赁对象的属性值为第二值。因此,本发明采用第一用户的信用分,及与该第一用户为好友关系的第二用户的信用分,来综合体现第一用户的信用程度,得到的第一用户的综合信用程度能够更加全面、权威地表征第一用户的信用状况,故,根据第一用户的信用分和第二用户的信用分,对租赁对象的属性值进行调整,实现了对租赁对象的属性值更加有针对性、智能调整。
如图12所示,本发明实施例还提供一种服务器,该服务器可以包括上述租赁对象属性值调整装置。
参照图12,该服务器的硬件结构,可以包括:处理器1,通信接口2,存储器3和通信总线4;其中,处理器1、通信接口2、存储器3通过通信总线4完成相互间的通信;
在具体实现时,通信接口2可以为通信模块的接口,如GSM模块的接口;处理器1可能是一个中央处理器CPU,或者是特定集成电路ASIC(Application Specific Integrated Circuit),或者是被配置成实施本发明实施例的一个或多个集成电路;存储器3可能包含高速RAM存储器,也可能还包括非易失性存储器(non-volatile memory),例如至少一个磁盘存储器。
其中,处理器1具体用于:获取客户端发送的租赁对象浏览请求;租赁对象浏览请求,用于请求第一应用平台上的至少一个租赁对象的信息;
根据第一用户在第二应用平台的账号,获取第一用户在第二应用平台的关系链;
根据关系链,确定与第一用户在第二应用平台为好友关系的第二用户;
根据第一用户和第二用户在第二应用平台的账号,分别获取第一用户及第二用户在第二应用平台的信用分;
根据第一用户的信用分,及第二用户的信用分,将租赁对象的属性值由第一值调整为第二值;其中,租赁对象的第一值从第一应用平台的属性值数据库中调取;
向客户端反馈租赁对象浏览页面,租赁对象浏览页面中指示租赁对象的属性值为第二值。
本发明实施例还提供了一种租赁对象属性值调整设备,该设备包括:
处理器以及存储器;
存储器,用于存储程序代码,并将程序代码传输给所述处理器;
处理器,用于根据上述程序代码中的指令执行上述租赁对象属性值调整方法。
本发明实施例还提供了一种存储介质,存储介质用于存储程序代码,程序代码用于执行上述租赁对象属性值调整方法。
本发明实施例还提供了一种包括指令的计算机程序产品,当其在计算机上运行时,使得计算机执行上述租赁对象属性值调整方法。
本发明实施例还提供了一种租赁对象属性值调整方法,应用于服务器,该方法包括:
服务器获取客户端发送的租赁对象浏览请求;租赁对象浏览请求,用于请求第一应用平台上的至少一个租赁对象的信息;
服务器根据的第一用户在第二应用平台的账号,确定与第一用户在第二应用平台为好友关系的第二用户;
服务器根据第一用户和第二用户在第二应用平台的账号,分别获取第一用户及第二用户在第二应用平台的信用分;
服务器根据第一用户的信用分,及第二用户的信用分,将租赁对象的属性值由第一值调整为第二值;其中,租赁对象的第一值从第一应用平台的属性值数据库中调取;
服务器向客户端反馈租赁对象浏览页面,租赁对象浏览页面中指示租赁对象的属性值为第二值。
其中,第一值与第二值的比值,与第一用户的信用分和第二用户的信用分为正相关关系。
一种可能的实现方式下,服务器根据第一用户在第二应用平台的账号,获取第一用户在第二应用平台的关系链;其中,第一用户以在第二应用平台的账号,登录第一应用平台;
服务器根据关系链,确定与第一用户在第二应用平台为好友关系的第二用户。
一种可能的实现方式下,服务器根据关系链,确定与第一用户在第二应用平台为好友关系的第二用户包括:
服务器根据关系链,确定与第一用户为直接好友关系的候选好友用户;
服务器根据第一用户在第二应用平台的账号,获取第一用户与各候选好友用户在第二应用平台的历史互动数据;
服务器根据第一用户与各候选好友用户的历史互动数据,确定第一用户与各候选好友用户的亲密度;
服务器从各候选好友用户中,选取亲密度符合设定亲密度条件的第二用户。
一种可能的实现方式下,服务器根据关系链,确定与第一用户为直接好友关系的候选好友用户包括:
服务器根据第一用户在第二应用平台的账号,获取第一用户在第二应用的社群信息,并从第一用户的社群中选取k个社群;
服务器根据关系链,从所选取的各社群中,确定与第一用户为直接好友关系的候选好友用户;
服务器根据第一用户在第二应用平台的账号,获取第一用户与各候选好友用户在第二应用平台的历史互动数据包括:
服务器根据第一用户在第二应用平台的账号,获取第一用户与所选取的各社群中的各候选好友用户的历史互动数据;
服务器根据第一用户与各候选好友用户的历史互动数据,确定第一用户与各候选好友用户的亲密度包括:
服务器根据第一用户与所选取的各社群中的各候选好友用户的历史互动数据,确定第一用户与所选取的各社群中的各候选好友用户的亲密度;
服务器从各候选好友用户中,选取亲密度符合设定亲密度条件的第二用户包括:
服务器从所选取的各社群中,分别选取与第一用户的亲密度最高的至少一个候选好友用户,得到m个第二用户,其中,m大于k。
一种可能的实现方式下,服务器从所选取的各社群中,分别选取与第一用户的亲密度最高的至少一个候选好友用户,得到m个第二用户包括:
服务器从与第一用户的亲密度最高的候选好友用户所在的社群中,选取与第一用户的亲密度最高的前m-k+1个候选好友用户;
服务器从剩余的k-1个社群中,分别选取与第一用户的亲密度最高的候选好友用户。
一种可能的实现方式下,服务器根据第一用户的信用分,及第二用户的信用分,将租赁对象的属性值由第一值调整为第二值包括:
服务器将信用分的取值范围划分区间,确定出信用分的多个分布区间;
服务器根据各第二用户的信用分,确定各第二用户的信用分所处的信用分的分布区间,得到第二用户的信用分分布;
服务器根据第一用户的信用分、第二用户的信用分分布、第一用户的用户属性、租赁对象的对象属性,确定租赁对象的属性值为第二值,并将租赁对象的属性值由第一值调整为第二值。
一种可能的实现方式下,服务器根据第一用户的信用分,及第二用户的信用分,将租赁对象的属性值由第一值调整为第二值包括:
服务器确定m个第二用户的信用分分布,及第一用户的所有好友用户的信用分分布;
服务器根据第一用户的信用分、m个第二用户的信用分分布、第一用户的所有好友用户的信用分分布、第一用户的用户属性、租赁对象的对象属性,将租赁对象的属性值由第一值调整为第二值。
一种可能的实现方式下,服务器根据第一用户的信用分,及第二用户的信用分,将租赁对象的属性值由第一值调整为第二值包括:
服务器将第一用户的信用分与第二用户的信用分相综合,得到综合信用分;
服务器将设定信用分阈值与综合信用分的比值,乘以租赁对象的第一值,确定租赁对象的第二值。
本说明书中各个实施例采用递进的方式描述,每个实施例重点说明的都是与其他实施例的不同之处,各个实施例之间相同相似部分互相参见即可。对于实施例公开的装置而言,由于其与实施例公开的方法相对应,所以描述的比较简单,相关之处参见方法部分说明即可。
专业人员还可以进一步意识到,结合本文中所公开的实施例描述的各示例的单元及算法步骤,能够以电子硬件、计算机软件或者二者的结合来实现,为了清楚地说明硬件和软件的可互换性,在上述说明中已经按照功能一般性地描述了各示例的组成及步骤。这些功能究竟以硬件还是软件方式来执行,取决于技术方案的特定应用和设计约束条件。专业技术人员可以对每个特定的应用来使用不同方法来实现所描述的功能,但是这种实现不应认为超出本发明的范围。
结合本文中所公开的实施例描述的方法或算法的步骤可以直接用硬件、处理器执行的软件模块,或者二者的结合来实施。软件模块可以置于随机存储器(RAM)、内存、只读存储器(ROM)、电可编程ROM、电可擦除可编程ROM、寄存器、硬盘、可移动磁盘、CD-ROM、或技术领域内所公知的任意其它形式的存储介质中。
对所公开的实施例的上述说明,使本领域专业技术人员能够实现或使用本发明。对这些实施例的多种修改对本领域的专业技术人员来说将是显而易见的,本文中所定义的一般原理可以在不脱离本发明的核心思想或范围的情况下,在其它实施例中实现。因此,本发明将不会被限制于本文所示的这些实施例,而是要符合与本文所公开的原理和新颖特点相一致的最宽的范围。

Claims (31)

  1. 一种租赁对象属性值调整方法,包括:
    获取客户端发送的租赁对象浏览请求;所述租赁对象浏览请求,用于请求第一应用平台上的至少一个租赁对象的信息;
    根据第一用户在第二应用平台的账号,确定与所述第一用户在所述第二应用平台为好友关系的第二用户;
    根据所述第一用户和所述第二用户在所述第二应用平台的账号,分别获取所述第一用户及所述第二用户在所述第二应用平台的信用分;
    根据所述第一用户的信用分,及所述第二用户的信用分,将所述租赁对象的属性值由第一值调整为第二值;其中,所述租赁对象的第一值从所述第一应用平台的属性值数据库中调取;
    向所述客户端反馈租赁对象浏览页面,所述租赁对象浏览页面中指示所述租赁对象的属性值为所述第二值。
  2. 根据权利要求1所述的方法,所述确定与所述第一用户在所述第二应用平台为好友关系的第二用户包括:
    根据所述第一用户在所述第二应用平台的账号,获取所述第一用户在所述第二应用平台的关系链;其中,所述第一用户以在第二应用平台的账号,登录所述第一应用平台;
    根据所述关系链,确定与所述第一用户在所述第二应用平台为好友关系的第二用户。
  3. 根据权利要求1所述的租赁对象属性值调整方法,所述第一值与所述第二值的比值,与所述第一用户的信用分及所述第二用户的信用分为正相关关系。
  4. 根据权利要求1所述的租赁对象属性值调整方法,所述根据所述关系链,确定与所述第一用户在所述第二应用平台为好友关系的第二用户包括:
    根据所述关系链,确定与所述第一用户为直接好友关系的候选好友用户;
    根据所述第一用户在所述第二应用平台的账号,获取所述第一用户与各所述候选好友用户在所述第二应用平台的历史互动数据;
    根据所述第一用户与各所述候选好友用户的历史互动数据,确定所述第一用户与各所述候选好友用户的亲密度;
    从各所述候选好友用户中,选取亲密度符合设定亲密度条件的所述第二用户。
  5. 根据权利要求4所述的租赁对象属性值调整方法,所述根据所述关系链,确定与所述第一用户为直接好友关系的候选好友用户包括:
    根据所述第一用户在所述第二应用平台的账号,获取所述第一用户在所述第二应用的社群信息,并从所述第一用户的社群中选取k个社群;
    根据所述关系链,从所选取的各社群中,确定与所述第一用户为直接好友关系的候选好友用户;
    所述根据所述第一用户在所述第二应用平台的账号,获取所述第一用户与各所述候选 好友用户在所述第二应用平台的历史互动数据包括:
    根据所述第一用户在所述第二应用平台的账号,获取所述第一用户与所选取的各社群中的各所述候选好友用户的历史互动数据;
    所述根据所述第一用户与各所述候选好友用户的历史互动数据,确定所述第一用户与各所述候选好友用户的亲密度包括:
    根据所述第一用户与所选取的各社群中的各所述候选好友用户的历史互动数据,确定所述第一用户与所选取的各社群中的各所述候选好友用户的亲密度;
    所述从各所述候选好友用户中,选取亲密度符合设定亲密度条件的第二用户包括:
    从所选取的各社群中,分别选取与所述第一用户的亲密度最高的至少一个所述候选好友用户,得到m个所述第二用户,其中,m大于k。
  6. 根据权利要求5所述的租赁对象属性值调整方法,所述从所选取的各社群中,分别选取与所述第一用户的亲密度最高的至少一个所述候选好友用户,得到m个所述第二用户包括:
    从与所述第一用户的亲密度最高的所述候选好友用户所在的社群中,选取与所述第一用户的亲密度最高的前m-k+1个所述候选好友用户;
    从剩余的k-1个社群中,分别选取与第一用户的亲密度最高的一个所述候选好友用户。
  7. 根据权利要求1-6任意一项所述的租赁对象属性值调整方法,所述根据所述第一用户的信用分,及所述第二用户的信用分,将所述租赁对象的属性值由第一值调整为第二值包括:
    将信用分的取值范围划分区间,确定出所述信用分的多个分布区间;
    根据各所述第二用户的信用分,确定各所述第二用户的信用分所处的信用分的分布区间,得到所述第二用户的信用分分布;
    根据所述第一用户的信用分、所述第二用户的信用分分布、所述第一用户的用户属性、所述租赁对象的对象属性,将租赁对象的属性值由第一值调整为第二值。
  8. 根据权利要求5或6所述的租赁对象属性值调整方法,所述根据所述第一用户的信用分,及所述第二用户的信用分,将所述租赁对象的属性值由第一值调整为第二值包括:
    确定所述m个第二用户的信用分分布,及所述第一用户的所有好友用户的信用分分布;
    根据所述第一用户的信用分、所述m个第二用户的信用分分布、所述第一用户的所有好友用户的信用分分布、所述第一用户的用户属性、所述租赁对象的对象属性,将租赁对象的属性值由第一值调整为第二值。
  9. 根据权利要求3所述的租赁对象属性值调整方法,所述根据所述第一用户的信用分,及所述第二用户的信用分,将所述租赁对象的属性值由第一值调整为第二值包括:
    将所述第一用户的信用分与所述第二用户的信用分相综合,得到综合信用分;
    将设定信用分阈值与所示综合信用分的比值,乘以所述租赁对象的所述第一值,确定所述租赁对象的所述第二值。
  10. 一种租赁对象属性值调整装置,包括:
    请求获取模块,用于获取客户端发送的租赁对象浏览请求;所述租赁对象浏览请求,用于请求第一应用平台上的至少一个租赁对象的信息;
    第二用户确定模块,用于根据第一用户在第二应用平台的账号,确定与所述第一用户在所述第二应用平台为好友关系的第二用户;
    信用分获取模块,用于根据所述第一用户和所述第二用户在所述第二应用平台的账号,分别获取所述第一用户及所述第二用户在所述第二应用平台的信用分;
    属性值调整模块,用于根据所述第一用户的信用分,及所述第二用户的信用分,将所述租赁对象的属性值由第一值调整为第二值;其中,所述租赁对象的第一值从所述第一应用平台的属性值数据库中调取;
    页面反馈模块,用于向所述客户端反馈租赁对象浏览页面,所述租赁对象浏览页面中指示所述租赁对象的属性值为所述第二值。
  11. 根据权利要求10所述的租赁对象属性值调整装置,所述第二用户确定模块,包括:
    关系链获取子模块,用于根据所述第一用户在所述第二应用平台的账号,获取所述第一用户在所述第二应用平台的关系链;其中,所述第一用户以在第二应用平台的账号,登录所述第一应用平台;
    第二用户确定子模块,用于根据所述关系链,确定与所述第一用户在所述第二应用平台为好友关系的第二用户。
  12. 根据权利要求10所述的租赁对象属性值调整装置,所述第一值与所述第二值的比值,与所述第一用户的信用分及所述第二用户的信用分成正相关关系。
  13. 根据权利要求10所述的租赁对象属性值调整装置,所述第二用户确定子模块,用于根据所述关系链,确定与所述第一用户在所述第二应用平台为好友关系的第二用户,具体包括:
    第一确定单元,用于根据所述关系链,确定与所述第一用户为直接好友关系的候选好友用户;
    第一获取单元,用于根据所述第一用户在所述第二应用平台的账号,获取所述第一用户与各所述候选好友用户在所述第二应用平台的历史互动数据;
    第二确定单元,用于根据所述第一用户与各所述候选好友用户的历史互动数据,确定所述第一用户与各所述候选好友用户的亲密度;
    选取单元,用于从各所述候选好友用户中,选取亲密度符合设定亲密度条件的所述第二用户。
  14. 根据权利要求13所述的租赁对象属性值调整装置,所述第一确定单元,包括:
    第一获取子单元,用于根据所述第一用户在所述第二应用平台的账号,获取所述第一用户在所述第二应用的社群信息,并从所述第一用户的社群中选取k个社群;
    第一确定子单元,用于根据所述关系链,从所选取的各社群中,确定与所述第一用户 为直接好友关系的候选好友用户;
    所述第一获取单元,包括:
    第二获取子单元,用于根据所述第一用户在所述第二应用平台的账号,获取所述第一用户与所选取的各社群中的各所述候选好友用户的历史互动数据;
    所述第二确定单元,包括:
    第二确定子单元,用于根据所述第一用户与所选取的各社群中的各所述候选好友用户的历史互动数据,确定所述第一用户与所选取的各社群中的各所述候选好友用户的亲密度;
    所述选取单元,包括:
    选取子单元,用于从所选取的各社群中,分别选取与所述第一用户的亲密度最高的至少一个所述候选好友用户,得到m个所述第二用户,其中,m大于k。
  15. 根据权利要求14所述的租赁对象属性值调整装置,所述选取子单元,包括:
    第一选取子单元,用于从与所述第一用户的亲密度最高的所述候选好友用户所在的社群中,选取与所述第一用户的亲密度最高的前m-k+1个所述候选好友用户;
    第二选取子单元,用于从剩余的k-1个社群中,分别选取与第一用户的亲密度最高的一个所述候选好友用户。
  16. 根据权利要求10-15任意一项所述的租赁对象属性值调整装置,所述属性值调整模块,用于根据所述第一用户的信用分,及所述第二用户的信用分,将所述租赁对象的属性值由第一值调整为第二值,具体包括:
    将信用分的取值范围划分区间,确定出所述信用分的多个分布区间;
    根据各所述第二用户的信用分,确定各所述第二用户的信用分所处的信用分的分布区间,得到所述第二用户的信用分分布;
    根据所述第一用户的信用分、所述第二用户的信用分分布、所述第一用户的用户属性、所述租赁对象的对象属性,将租赁对象的属性值由第一值调整为第二值。
  17. 根据权利要求14或15所述的租赁对象属性值调整装置,所述属性值调整模块,包括:
    信用分确定子模块,用于确定所述m个第二用户的信用分分布,及所述第一用户的所有好友用户的信用分分布;
    属性值调整子模块,用于根据所述第一用户的信用分、所述m个第二用户的信用分分布、所述第一用户的所有好友用户的信用分分布、所述第一用户的用户属性、所述租赁对象的对象属性,将租赁对象的属性值由第一值调整为第二值。
  18. 根据权利要求12所述的租赁对象属性值调整装置,所述属性值调整模块,包括:
    综合子模块,用于将所述第一用户的信用分与所述第二用户的信用分相综合,得到综合信用分;
    计算子模块,用于将设定信用分阈值与所示综合信用分的比值,乘以所述租赁对象的所述第一值,确定所述租赁对象的所述第二值。
  19. 一种服务器,包括权利要求10-18任意一项所述的租赁对象属性值调整装置。
  20. 一种租赁对象属性值调整方法,应用于服务器,所述方法包括:
    服务器获取客户端发送的租赁对象浏览请求;所述租赁对象浏览请求,用于请求第一应用平台上的至少一个租赁对象的信息;
    服务器根据所述第一用户在第二应用平台的账号,确定与所述第一用户在所述第二应用平台为好友关系的第二用户;
    服务器根据所述第一用户和所述第二用户在所述第二应用平台的账号,分别获取所述第一用户及所述第二用户在所述第二应用平台的信用分;
    服务器根据所述第一用户的信用分,及所述第二用户的信用分,将所述租赁对象的属性值由第一值调整为第二值;其中,所述租赁对象的第一值从所述第一应用平台的属性值数据库中调取;
    服务器向所述客户端反馈租赁对象浏览页面,所述租赁对象浏览页面中指示所述租赁对象的属性值为所述第二值。
  21. 根据权利要求20所述的租赁对象属性值调整方法,应用于服务器,
    服务器根据所述第一用户在所述第二应用平台的账号,获取所述第一用户在所述第二应用平台的关系链;其中,所述第一用户以在第二应用平台的账号,登录所述第一应用平台;
    服务器根据所述关系链,确定与所述第一用户在所述第二应用平台为好友关系的第二用户。
  22. 根据权利要求20所述的租赁对象属性值调整方法,应用于服务器,所述第一值与所述第二值的比值,与所述第一用户的信用分和所述第二用户的信用分为正相关关系。
  23. 根据权利要求20所述的租赁对象属性值调整方法,所述服务器根据所述关系链,确定与所述第一用户在所述第二应用平台为好友关系的第二用户包括:
    服务器根据所述关系链,确定与所述第一用户为直接好友关系的候选好友用户;
    服务器根据所述第一用户在所述第二应用平台的账号,获取所述第一用户与各所述候选好友用户在所述第二应用平台的历史互动数据;
    服务器根据所述第一用户与各所述候选好友用户的历史互动数据,确定所述第一用户与各所述候选好友用户的亲密度;
    服务器从各所述候选好友用户中,选取亲密度符合设定亲密度条件的所述第二用户。
  24. 根据权利要求23所述的租赁对象属性值调整方法,所述服务器根据所述关系链,确定与所述第一用户为直接好友关系的候选好友用户包括:
    服务器根据所述第一用户在所述第二应用平台的账号,获取所述第一用户在所述第二应用的社群信息,并从所述第一用户的社群中选取k个社群;
    服务器根据所述关系链,从所选取的各社群中,确定与所述第一用户为直接好友关系的候选好友用户;
    所述服务器根据所述第一用户在所述第二应用平台的账号,获取所述第一用户与各所述候选好友用户在所述第二应用平台的历史互动数据包括:
    服务器根据所述第一用户在所述第二应用平台的账号,获取所述第一用户与所选取的各社群中的各所述候选好友用户的历史互动数据;
    所述服务器根据所述第一用户与各所述候选好友用户的历史互动数据,确定所述第一用户与各所述候选好友用户的亲密度包括:
    服务器根据所述第一用户与所选取的各社群中的各所述候选好友用户的历史互动数据,确定所述第一用户与所选取的各社群中的各所述候选好友用户的亲密度;
    所述服务器从各所述候选好友用户中,选取亲密度符合设定亲密度条件的第二用户包括:
    服务器从所选取的各社群中,分别选取与所述第一用户的亲密度最高的至少一个所述候选好友用户,得到m个所述第二用户,其中,m大于k。
  25. 根据权利要求24所述的租赁对象属性值调整方法,所述服务器从所选取的各社群中,分别选取与所述第一用户的亲密度最高的至少一个所述候选好友用户,得到m个所述第二用户包括:
    服务器从与所述第一用户的亲密度最高的所述候选好友用户所在的社群中,选取与所述第一用户的亲密度最高的前m-k+1个所述候选好友用户;
    服务器从剩余的k-1个社群中,分别选取与第一用户的亲密度最高的候选好友用户。
  26. 根据权利要求20-25任意一项所述的租赁对象属性值调整方法,所述服务器根据所述第一用户的信用分,及所述第二用户的信用分,将所述租赁对象的属性值由第一值调整为第二值包括:
    服务器将信用分的取值范围划分区间,确定出所述信用分的多个分布区间;
    服务器根据各所述第二用户的信用分,确定各所述第二用户的信用分所处的信用分的分布区间,得到所述第二用户的信用分分布;
    服务器根据所述第一用户的信用分、所述第二用户的信用分分布、所述第一用户的用户属性、所述租赁对象的对象属性,确定所述租赁对象的属性值为第二值,并将租赁对象的属性值由第一值调整为第二值。
  27. 根据权利要求24或25所述的租赁对象属性值调整方法,所述服务器根据所述第一用户的信用分,及所述第二用户的信用分,将所述租赁对象的属性值由第一值调整为第二值包括:
    服务器确定所述m个第二用户的信用分分布,及所述第一用户的所有好友用户的信用分分布;
    服务器根据所述第一用户的信用分、所述m个第二用户的信用分分布、所述第一用户的所有好友用户的信用分分布、所述第一用户的用户属性、所述租赁对象的对象属性,将租赁对象的属性值由第一值调整为第二值。
  28. 根据权利要求22所述的租赁对象属性值调整方法,所述服务器根据所述第一用户的信用分,及所述第二用户的信用分,将所述租赁对象的属性值由第一值调整为第二值包括:
    服务器将所述第一用户的信用分与所述第二用户的信用分相综合,得到综合信用分;
    服务器将设定信用分阈值与所述综合信用分的比值,乘以所述租赁对象的所述第一值,确定所述租赁对象的所述第二值。
  29. 一种租赁对象属性值调整设备,所述设备包括:
    处理器以及存储器;
    所述存储器,用于存储程序代码,并将所述程序代码传输给所述处理器;
    所述处理器,用于根据所述程序代码中的指令执行权利要求1-9任意一项所述的租赁对象属性值调整方法。
  30. 一种存储介质,所述存储介质用于存储程序代码,所述程序代码用于执行权利要求1-9任意一项所述的租赁对象属性值调整方法。
  31. 一种包括指令的计算机程序产品,当其在计算机上运行时,使得所述计算机执行权利要求1-9任意一项所述的租赁对象属性值调整方法。
PCT/CN2017/107300 2016-11-18 2017-10-23 租赁对象属性值调整方法、装置及服务器 WO2018090788A1 (zh)

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