Big data analysis-based indemnificatory rental house management system

Abstract

The invention relates to the technical field of lease transaction, and discloses a big data analysis-based indemnificatory lease house management system, which is composed of an applicant information acquisition module, a house resource information acquisition module, an information verification mechanism module, a matching degree calculation module and a dynamic adjustment mechanism module. Through a comprehensive score calculation formula, the system converts basic information, demand information, income proof and family member information into a comprehensive score S. The housing resource information acquisition module ensures basic information and dynamic information of housing resources: position, area, rent, available state and repair record. It is ensured that the applicant does not apply repeatedly or exceeds the allowed application number, so that the problems of waste of system resources and repeated matching of the applicant are avoided, and the beneficial effects of verifying the information mechanism of the applicant and ensuring that the applicant accurately matches the rental house with true intention are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of leasing transactions, and in particular to an affordable rental housing management system based on big data analysis. Background Art

[0002] With the advancement of urbanization, the demand for affordable rental housing is increasing. How to effectively allocate limited affordable rental housing resources to the people who need them most has become an urgent problem to be solved. The traditional method of matching people with affordable rental housing is usually to manually review the applicant's information and then conduct preliminary screening based on factors such as the applicant's family situation, income level, and housing needs. After that, people and houses are matched based on the screened applicant information and the information of affordable rental housing sources. However, this method has the following problems: Low efficiency of manual review: Due to the large number of applicants, the efficiency of manual review is low and cannot meet the needs of large-scale affordable rental housing matching. Incomplete information: In traditional methods, the acquisition of applicant and housing information mainly depends on the materials submitted by the applicant and the information registration of the affordable housing management department. This information is often incomplete, which affects the accuracy of people and houses matching. Low matching accuracy: In traditional methods, people and houses matching mainly relies on manual experience, which is easily affected by subjective factors, resulting in low accuracy of matching results. In the prior art, when organizing viewings of affordable rental housing, people and houses are often matched only based on the housing sources applied for by the applicants, and two-way matching between housing sources and applicants cannot be achieved.

[0003] The prior art discloses a method, medium and system for matching people with affordable rental housing, belonging to the field of housing security technology. The method for matching people with affordable rental housing includes: obtaining applicant information according to basic information submitted by the applicant; obtaining basic information of affordable rental housing sources to obtain housing source information; calculating the matching degree of people with housing for different applicants for each housing source according to each applicant information and each housing source information; grouping applicants according to the matching degree of people with housing for each affordable rental housing source to obtain a matching data set for people with housing, which is used to arrange applicants to visit the housing on site later; the present invention can more accurately recommend affordable rental housing sources suitable for applicants, thereby improving the accuracy of people with housing matching; it can solve the technical problem that the existing technology mainly focuses on data collection and analysis, and the accuracy of people with housing matching is not high, and well solves the problem of two-way matching and the problem of precision.

[0004] However, the aforementioned technical solution collects applicant information and housing information for matching. However, the aforementioned technical solution does not have a mechanism to verify applicant information, and cannot prevent a single applicant from applying for multiple affordable rental houses with different information. This will not only cause confusion in the matching system but also cause the final matching data to contain multiple houses for one person, affecting the rental applications of other applicants. Summary of the invention

[0005] Technical issues solved: In view of the shortcomings of the prior art, the present invention provides an affordable rental housing management system based on big data analysis, which has the advantages of verifying the applicant's information mechanism to ensure that the applicant is accurately matched with the rental housing of real intention, and will not cause system matching confusion due to a single applicant applying for multiple rental houses at one time, thereby solving the above-mentioned technical problems.

[0006] Technical solution: To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a management system for affordable rental housing based on big data analysis, the management system comprising an applicant information collection module, a housing source information collection module, an information verification mechanism module, a matching degree calculation module and a dynamic adjustment mechanism module; The applicant information collection module is used to collect the applicant's basic information, needs, income proof and family member information; The housing information collection module is used to obtain and update the basic information of affordable rental housing, input the basic information of the housing, such as location, area and rent, and update the availability status and other dynamic information of the housing in real time; The information verification mechanism module is used to verify the authenticity of the applicant's information, compare the information provided by the applicant with the existing database information, verify the applicant's identity information through third-party authentication, detect whether the applicant has applied for other housing sources, and limit the number of applications; The matching degree calculation module is used to calculate the matching degree between the applicant and the housing source, calculate the matching degree according to the applicant's needs and the characteristics of the housing source, assign weights to different matching factors, generate a comprehensive score, and sort the applicants according to the matching degree; The dynamic adjustment mechanism module is used to process the application status of the applicant and the dynamic information of the housing resources, track the application status of the applicant in real time, update the available status of the housing resources, accept the applicant's feedback, and adjust the matching results.

[0007] Preferably, the applicant's comprehensive score calculation expression in the applicant information collection module is: The comprehensive score S is expressed as:

[0008] in: Represents the basic information score vector, score: name, age, gender; Represents the demand information score vector, score: room type, area, rental range; Represents the income proof score vector, score: monthly income, annual income; Represents the score vector of family member information, score: family size, member age; The weights are: Basic information weight ; Demand information weight ; Weight of income proof ; Weight of family member information .

[0009] Preferably, the data model expression of the housing information collection module is:

[0010] in: Indicates the location of the property. for location; Indicates the area of ​​the property. is the area; Indicates the rental price of the property. for rent; Indicates the status of the property. Available status: "Available" or "Rented"; Indicates dynamic information. For real-time update information: last update date and repair record.

[0011] Preferably, the real-time update expression in the housing information collection module is: Dynamic information about the property Include the following: Last updated date ; Repair records ; Dynamic information is represented as:

[0012] The status of the listing is updated based on the current situation:

[0013] in: It is the old status of the property; It is dynamic information; is a function that calculates the new listing status , according to dynamic information Update the status of your listing.

[0014] Preferably, the information provided by the applicant in the information verification mechanism module is:

[0015] in: Indicates identity information; Indicates detailed information for housing application; O indicates other relevant information: proof of income; The information currently in the database is:

[0016] The verification formula is expressed as:

[0017]

[0018]

[0019] in: Indicates the identity information verification result; Indicates the verification result of the detailed information of the housing application; Indicates other relevant information verification results; Is a comparison function used to check the provided information With database information degree of match.

[0020] Preferably, the third-party authentication verification expression in the information verification mechanism module is: The third-party certification results are:

[0021] in: Indicates the identity information authentication result; Indicates the authentication result of the detailed information of the applied house; The authentication formula is expressed as:

[0022] in: Indicates the third-party authentication verification result.

[0023] Preferably, the expression for detecting whether the applicant has applied for other housing sources in the information verification mechanism module is: The applied property record is:

[0024] The detection formula is:

[0025] in: Indicates whether the test results of other properties have been applied for; is a comparison function used to check the overlap between the applicant's current application and historical applications; The expression for limiting the number of applications is: Assume the maximum number of applications allowed is: The number of applications is: ; The limiting formula is:

[0026] in: A flag indicating whether the application is allowed. Indicates permission, Indicates not allowed.

[0027] Preferably, the matching degree calculation expression in the matching degree calculation module is: The applicant's required information is:

[0028] in: Indicates Demand characteristics; The property's characteristic information is:

[0029] in: Indicates Features of the property; The weight of each matching factor is:

[0030] in: Indicates The weight of each matching factor; The matching degree M is expressed as:

[0031] in: is the computational demand characteristic and listing features Function of the degree of matching.

[0032] Preferably, the comprehensive score expression in the matching degree calculation module is: If there are other additional scoring factors and its weight , comprehensive rating It is expressed as:

[0033] in: Indicates the scoring factor The weight of Indicates additional scoring factors.

[0034] Preferably, the dynamic adjustment mechanism is expressed as: Real-time tracking of application status and listing dynamic information: Assume the applicant's application status is:

[0035] in: Indicates the ID of the applicant; Indicates the status of the application: "pending", "approved" or "rejected"; Indicates the applicant's feedback: "satisfied" or "unsatisfied".

[0036] Compared with the prior art, the present invention provides an affordable rental housing management system based on big data analysis, which has the following beneficial effects: 1. The present invention uses a comprehensive score calculation formula to convert basic information, demand information, income proof and family member information into a comprehensive score S. The housing information collection module ensures that the basic information and dynamic information of the housing: location, area, rent, availability and repair record are updated in real time. The real-time nature avoids the problem of outdated information and ensures that applicants can see the latest housing information, thereby improving the accuracy of matching. The information verification mechanism module compares the information provided by the applicant with the information in the existing database and uses a third-party authentication to verify the applicant's identity information, detects whether the applicant has applied for other housing sources and limits the number of applications, and ensures that the applicant will not apply repeatedly or exceed the allowed number of applications, thereby avoiding the waste of system resources and the problem of repeated matching of applicants, and achieving the beneficial effect of verifying the applicant's information mechanism to ensure that the applicant is accurately matched to the real intended rental house.

[0037] 2. The present invention includes a detection of whether the applicant has applied for other housing sources in the information verification mechanism module. The system can detect whether the applicant has applied for duplicate applications by comparing the applicant's current application record with the historical application record, thereby preventing an applicant from applying for multiple housing sources at the same time, thereby avoiding system matching confusion caused by duplicate applications. The dynamic adjustment mechanism module tracks the applicant's application status in real time and updates the available status of the housing source. The system ensures that the applicant's application information is the latest by updating the application status and housing source status in real time, reducing matching problems caused by changes in housing source status. Through the comprehensive scoring and matching degree calculation module, the system can calculate the matching degree based on the applicant's real needs and the actual characteristics of the housing source, achieving the beneficial effect of not causing system matching confusion due to a single applicant applying for multiple rental houses at one time. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a schematic diagram of the system of the present invention; DETAILED DESCRIPTION The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0039] See also Figure 1 , a management system for affordable rental housing based on big data analysis, the management system comprising an applicant information collection module, a housing source information collection module, an information verification mechanism module, a matching degree calculation module and a dynamic adjustment mechanism module; The applicant information collection module is used to collect the applicant's basic information, needs, income proof and family member information; The housing information collection module is used to obtain and update the basic information of affordable rental housing, input the basic information of the housing, such as location, area and rent, and update the availability status and other dynamic information of the housing in real time; The information verification mechanism module is used to verify the authenticity of the applicant's information, compare the information provided by the applicant with the existing database information, verify the applicant's identity information through third-party authentication, detect whether the applicant has applied for other housing sources, and limit the number of applications; The matching degree calculation module is used to calculate the matching degree between the applicant and the housing source, calculate the matching degree according to the applicant's needs and the characteristics of the housing source, assign weights to different matching factors, generate a comprehensive score, and sort the applicants according to the matching degree; The dynamic adjustment mechanism module is used to process the application status of the applicant and the dynamic information of the housing resources, track the application status of the applicant in real time, update the available status of the housing resources, accept the applicant's feedback, and adjust the matching results.

[0040] The applicant information collection module collects the applicant's basic information, needs, income proof and family member information. Comprehensive data collection ensures that the system can obtain the applicant's complete background and thus match their needs more accurately.

[0041] Comprehensive score calculation: Through the comprehensive score calculation formula, the system converts basic information, demand information, income proof and family member information into a comprehensive score S. The scoring mechanism helps the system quantify the comprehensive conditions of the applicant, making the matching process more scientific.

[0042] Real-time update: The property information collection module ensures that the basic and dynamic information of the property is updated in real time. The real-time nature avoids the problem of outdated information and ensures that applicants can see the latest property information, thereby improving the accuracy of matching.

[0043] Authenticity verification: The information verification mechanism module compares the information provided by the applicant with the information in the existing database and uses third-party authentication to verify the applicant's identity information. The verification method ensures the authenticity and reliability of the applicant's information and reduces the risk of false applications.

[0044] Detection of duplicate applications: The mechanism of detecting whether an applicant has applied for other properties and limiting the number of applications ensures that an applicant does not apply repeatedly or exceed the allowed number of applications, thereby avoiding waste of system resources and duplicate matching of applicants.

[0045] Accurate matching: The matching degree calculation module calculates the matching degree between the applicant's needs and the characteristics of the house, and assigns weights to different matching factors to generate a comprehensive score. This method ensures that the matching degree calculation is based on the applicant's specific needs and the actual characteristics of the house, making the matching results more accurate and reasonable.

[0046] Comprehensive score: In addition to calculating the matching degree, the comprehensive score also takes into account additional scoring factors to further improve the comprehensiveness and accuracy of the matching results.

[0047] Real-time adjustment: The dynamic adjustment mechanism module tracks the applicant's application status and the dynamic information of the house in real time, and adjusts the matching results according to the applicant's feedback. The mechanism ensures that when the applicant's status or house information changes, the system can adjust the matching results in time, making the matching process more flexible and in line with the actual situation.

[0048] The information verification mechanism module includes a check on whether the applicant has applied for other properties. By comparing the applicant's current application record with the historical application record, the system can detect whether the applicant has applied for duplicate properties. The detection mechanism prevents an applicant from applying for multiple properties at the same time, thus avoiding system matching confusion caused by duplicate applications.

[0049] Limit the number of applications: The mechanism also sets the maximum number of applications allowed, and uses a limiting formula to mark the situation where the number of applications is exceeded. If the actual number of applications of an applicant exceeds the maximum number allowed, the system will automatically limit the applicant from continuing to apply, thus avoiding the situation of applying for too many properties. This measure effectively curbs the behavior of applicants applying for multiple properties at one time and reduces confusion in the matching process.

[0050] Real-time tracking and updating: The dynamic adjustment mechanism module tracks the applicant's application status in real time and updates the availability of housing. The system ensures that the applicant's application information is up to date by updating the application status and housing status in real time, reducing matching problems caused by changes in housing status.

[0051] Third-party authentication: To further verify the authenticity of the applicant, the system verifies the applicant's identity information and housing application details through a third-party authentication. This ensures the authenticity and consistency of the information provided by the applicant, and further prevents matching confusion in the system due to false or duplicate applications.

[0052] Comprehensive scoring: Through the comprehensive scoring and matching calculation module, the system can calculate the matching degree based on the applicant's real needs and the actual characteristics of the house. The calculation method helps the system give priority to those applicants who really meet the requirements, avoiding matching confusion caused by applicants applying for multiple houses at the same time.

[0053] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A management system for affordable rental housing based on big data analysis, characterized in that: The management system is composed of an applicant information collection module, a housing information collection module, an information verification mechanism module, a matching degree calculation module and a dynamic adjustment mechanism module; The applicant information collection module is used to collect the applicant's basic information, needs, income proof and family member information; The housing information collection module is used to obtain and update the basic information of affordable rental housing, input the basic information of the housing, such as location, area and rent, and update the availability status and other dynamic information of the housing in real time; The information verification mechanism module is used to verify the authenticity of the applicant's information, compare the information provided by the applicant with the existing database information, verify the applicant's identity information through third-party authentication, detect whether the applicant has applied for other housing sources, and limit the number of applications; The matching degree calculation module is used to calculate the matching degree between the applicant and the housing source, calculate the matching degree according to the applicant's needs and the characteristics of the housing source, assign weights to different matching factors, generate a comprehensive score, and sort the applicants according to the matching degree; The dynamic adjustment mechanism module is used to process the application status of the applicant and the dynamic information of the housing resources, track the application status of the applicant in real time, update the available status of the housing resources, accept the applicant's feedback, and adjust the matching results.

2. The affordable rental housing management system based on big data analysis according to claim 1 is characterized by: The calculation expression of the applicant's comprehensive score in the applicant information collection module is: The comprehensive score S is expressed as: in: Represents the basic information score vector, score: name, age, gender; Represents the demand information score vector, score: room type, area, rental range; Represents the income proof score vector, score: monthly income, annual income; Represents the score vector of family member information, score: family size, member age; The weights are: Basic information weight ; Demand information weight ; Weight of income proof ; Weight of family member information .

3. The affordable rental housing management system based on big data analysis according to claim 2 is characterized by: The data model expression of the housing information collection module is: in: Indicates the location of the property. for location; Indicates the area of ​​the property. is the area; Indicates the rental price of the property. for rent; Indicates the status of the property. Available status: "Available" or "Rented"; Indicates dynamic information. For real-time update information: last update date and repair record.

4. The affordable rental housing management system based on big data analysis according to claim 3 is characterized by: The real-time update expression in the housing information collection module is: Dynamic information about the property Include the following: Last updated date ; Repair records ; Dynamic information is represented as: The status of the listing is updated based on the current situation: in: It is the old status of the property; It is dynamic information; is a function that calculates the new listing status , according to dynamic information Update the status of your listing.

5. The affordable rental housing management system based on big data analysis according to claim 1 is characterized by: The information provided by the applicant in the information verification mechanism module is: in: Indicates identity information; Indicates detailed information for housing application; O indicates other relevant information: proof of income; The information currently in the database is: The verification formula is expressed as: in: Indicates the identity information verification result; Indicates the verification result of the detailed information of the housing application; Indicates other relevant information verification results; Is a comparison function used to check the provided information With database information degree of match.

6. The affordable rental housing management system based on big data analysis according to claim 5 is characterized by: The third-party authentication verification expression in the information verification mechanism module is: The third-party certification results are: in: Indicates the identity information authentication result; Indicates the authentication result of the detailed information of the applied house; The authentication formula is expressed as: in: Indicates the third-party authentication verification result.

7. The affordable rental housing management system based on big data analysis according to claim 6 is characterized by: The expression for detecting whether the applicant has applied for other housing sources in the information verification mechanism module is: The applied property record is: The detection formula is: in: Indicates whether the test results of other properties have been applied for; is a comparison function used to check the overlap between the applicant's current application and historical applications; The expression for limiting the number of applications is: Assume the maximum number of applications allowed is: The number of applications is: ; The limiting formula is: in: A flag indicating whether the application is allowed. Indicates permission, Indicates not allowed.

8. The affordable rental housing management system based on big data analysis according to claim 1 is characterized by: The matching degree calculation expression in the matching degree calculation module is: The applicant's required information is: in: Indicates Demand characteristics; The property's characteristic information is: in: Indicates Features of the property; The weight of each matching factor is: in: Indicates The weight of each matching factor; The matching degree M is expressed as: in: is the computational demand characteristic and listing features Function of the degree of matching.

9. The affordable rental housing management system based on big data analysis according to claim 1 is characterized by: The comprehensive scoring expression in the matching degree calculation module is: If there are other additional scoring factors and its weight , comprehensive rating It is expressed as: in: Indicates the scoring factor The weight of Indicates additional scoring factors.

10. The affordable rental housing management system based on big data analysis according to claim 1 is characterized by: The dynamic adjustment mechanism is expressed as: Real-time tracking of application status and listing dynamic information: Assume the applicant's application status is: in: Indicates the ID of the applicant; Indicates the status of the application: "pending", "approved" or "rejected"; Indicates the applicant's feedback: "satisfied" or "unsatisfied".

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