House handling system based on big data

Abstract

The invention discloses a house handling system based on big data, which relates to the technical field of house handling and comprises a login module, a type analysis module, an authority granting module, an intra-area communication module, a house resource integration module, a travel index analysis module, a house area quality analysis module, a transaction platform module and a process display module. The system has the advantages that rich house choices can be provided for users through the house resource integration module, the house finding efficiency is greatly improved, the travel index can be judged according to the travel information of the residential quarter through the travel index analysis module, the users are helped to know the traffic convenience degree around the houses, and the user experience is improved. Important reference is provided for users with high travel requirements, the house area quality can be judged and the environment index can be calculated according to the environment of the living house area through the house area quality analysis module, the living environment factors can be fully considered when the users select houses, and the users can know the advantages and disadvantages of the houses in a more detailed mode.

Description

Technical Field

[0001] The present invention relates to the technical field of house purchasing, and in particular to a house purchasing system based on big data. Background Art

[0002] Houses are reinforced concrete buildings for living or storing things. Houses are the foundation of a family and the sustenance of human survival. Here people can avoid all external interference and enjoy freedom with their loved ones. Generally, it refers to a permanent place with a roof and walls around it, which can protect against wind and rain, keep out the cold and keep warm, and provide a place for people to work, live, study, entertain and store materials. It has a fixed foundation and a floor height of generally more than 2.2 meters. The use of houses should be divided according to the use specified in the design. If the house is related to residential and commercial business premises and has more than two uses, the building area should be calculated separately according to the use specified in the design.

[0003] When common house purchasing systems are used, housing information is often scattered among many different platforms, real estate companies and intermediary agencies, resulting in inefficient house hunting. When analyzing the convenience of travel, the comprehensive convenience of travel is not sufficiently considered. To this end, we propose a house purchasing system based on big data. Summary of the invention

[0004] The purpose of the present invention is to provide a house purchasing system based on big data.

[0005] In order to solve the problems raised in the above background technology, the present invention provides the following technical solutions: a house purchasing system based on big data, comprising a login module, the login module is used to register an account for a user, and also comprises a category analysis module, an authority granting module, an intra-district communication module, a house source integration module, a travel index analysis module and a house area quality analysis module;

[0006] The housing source integration module collects housing information and divides it into communities, then integrates the first-hand housing real estate companies and second-hand housing real estate agencies in each community, obtains the housing source information of the first-hand housing real estate companies and second-hand housing real estate agencies in each community, generates housing information, and shares the housing source information with the corresponding communities;

[0007] The travel index analysis module can extract house information, divide it into residential areas, obtain residential area information, and collect its travel information to determine the travel index;

[0008] Housing area quality analysis module, extracts residential area information, judges housing area quality according to the environment of the residential area, and calculates the housing area environment index;

[0009] Category analysis module, establishes second-hand housing units, rental housing units and new housing units, and users select housing purchase categories through second-hand housing units, rental housing units and new housing units, and obtain housing purchase location information;

[0010] The permission granting module establishes permission granting units, extracts user accounts, divides user accounts, obtains decentralized accounts, grants permissions to different decentralized accounts, and develops viewing panels for different permission types;

[0011] The intra-district communication module extracts housing information and then divides the housing information into communities, residential areas and single-family houses, thereby generating community areas, residential area areas and single-family house areas respectively, and establishing a communication platform for them.

[0012] As a further solution of the present invention: it also includes a transaction platform module and a process display module;

[0013] The trading platform module extracts house information, establishes a trading platform, divides house information according to the type of permissions, and then publishes the divided house information to the corresponding viewing panel;

[0014] The process display module can establish a general background processing unit, and establish national panel, provincial panel and city panel maps inside the main station processing unit, and establish city sections inside the city panel map. The homepage of the general background processing unit can clearly view the number of stores in each province across the country and the location of the stores in the current city map. Click the provincial panel to see the number of stores in each city in the current province. Click the city panel map to enter the city section. The city section displays the housing information of the current city and sets color difference labels for the housing information. The housing number, store data and housing data are recorded in blue, light blue and yellow labels respectively. When the mouse is placed on the blue, light blue and yellow dots, the housing number, store data and housing data can be directly viewed.

[0015] As a further solution of the present invention: after the housing source integration module shares the housing source information with the corresponding community, a multi-layer architecture is simultaneously established, wherein the multi-layer architecture includes a front-end display layer, a business logic layer and a data storage layer;

[0016] The front-end display layer can provide a friendly user interface for housing management office staff to view various information;

[0017] Business logic layer, which handles business operations such as data query, statistics, and audit;

[0018] The data storage layer is used to store information about real estate companies for first-hand housing, real estate agency companies for second-hand housing, and housing information;

[0019] The integrated first-hand real estate companies and second-hand real estate agencies must be registered with the housing management office within the jurisdiction. The housing management office can view the integrated first-hand real estate company information, second-hand real estate agency information, the current housing information of each company, and the housing information that has been sold in the past through the system.

[0020] As a further solution of the present invention: after obtaining the residential area information, the travel index analysis module will extract the area information of the residential area and the actual road width information surrounding the residential area, and calculate the road width data that does not affect the traffic of residents in the residential area. The standard of the number of traffic per hour on the surrounding roads is T 标准 , assuming that the number of vehicles passing through per hour during peak hours is M 通行 , assuming the traffic efficiency of the road is T 效率 , let the road width threshold be D 阈值 , assuming the ideal width of the road is D 理想 ;

[0021]

[0022] The above formula can be used to calculate the ideal width of the road, and at the same time, a road width threshold is established to limit the actual maximum road width. Suppose the road width threshold is D 阈值 , let the determined road width be D 判定 ;

[0023] When D 理想 >D 阈值 When the road width is determined, the road width threshold is used as the main factor. 阈值 It will cover D 判定 ;

[0024] When D 理想 ≤D 阈值 When the ideal width of the road is used as the main factor to determine the road width, D 理想 It will cover D 判定 ;

[0025] The road width can be determined according to the above method.

[0026] As a further solution of the present invention: after obtaining the determined road width, the travel index analysis module needs to calculate the ratio of the actual road width to the determined width, and comprehensively consider factors such as public transportation, shared travel tools, travel time cost and proximity to transportation hubs. Users can supplement the information in the factor expansion unit as needed to calculate the travel index of the residential area. Suppose the actual road width information is D 实际 , let the travel index be C Z , let the impact of the factor on the travel index be C Y , let the number of factors be M;

[0027]

[0028] The travel index of the residential area can be calculated according to the above formula.

[0029] As a further solution of the present invention: after extracting the residential area information, the housing area quality analysis module will analyze the green coverage area information, plant diversity information, environmental sanitation information, building density information and imaging density information in the residential area information, and set the ideal green coverage rate to be L 覆盖率 , let the vertical projection area of ​​the green area of ​​the residential area be J L , let the vertical projection area of ​​green space be S, let the floor area of ​​residential area be F 占地面积 , let the green coverage area index be L ZS ;

[0030]

[0031] Based on the above information, we can calculate the green coverage area index, plant diversity index, environmental sanitation index, building density index, image density index and advertising index. Let the number of advertisements not in the advertisement column be G. 数量 , let the number of solid surfaces in the residential area be L S , let the advertising index be G 指数 ;

[0032]

[0033] The advertising index can be calculated using the above formula.

[0034] As a further solution of the present invention: after calculating the advertising index, the housing area quality analysis module sets index weights for the green coverage area index, plant diversity index, environmental sanitation index, building density index and contrast density index, and converts the index weights for the green coverage area index, plant diversity index, environmental sanitation index, building density index and contrast density index into different factor indexes. Let the factor index be Y Z , let the number of factors be B, let the weights of different factor indexes be Z Q , let the housing area environment index be F 环境指数 , let the influence weight of advertising index be G 权重 ;

[0035]

[0036] According to the above formula, the housing area environment index can be calculated, where

[0037] As a further solution of the present invention: after obtaining the purchase location information of the house, the category analysis module will formulate a viewing interface according to the second-hand housing unit, the rental housing unit and the new housing unit to generate a multi-layer interface, and after dividing the user account, the permission granting module will obtain the general backend account, the direct store account, the store account, the community account, the housing management office account, the urban management account and the bank account;

[0038] The general backend account has the authority to view all second-hand housing location information, new housing location information, rental location information, small advertisement location information, salesperson location information, housekeeping staff location information and store location information across the country;

[0039] The permissions of the direct-sale store account can see all the second-hand housing location information, new housing location information, rental location information, small advertisement location information, salesperson location information, housekeeping staff location information and store location information across the country;

[0040] The store account has the authority to view the location information of the salesperson bound to the store, the location information of the second-hand houses, new houses, and rental houses managed by the store, the current location information of the store, and the city-level information of the current city;

[0041] The community account has the authority to view the second-hand housing location information, new housing location information, rental housing location information, and electronic advertising location information within the district or county;

[0042] The account of the Housing Management Office has the authority to view the location information of second-hand houses, new houses, rental houses, salespersons and stores within the district or county.

[0043] The permissions of the urban management account can see the location information of small advertisements within the district or county;

[0044] The bank account permissions allow you to view the location information of second-hand houses, new houses, and rental houses within your district or county.

[0045] As a further solution of the present invention: after the intra-district communication module generates the community area, the residential area and the single-family area, a community communication platform will be formulated for the community area, a community communication interface and a residential area communication platform will be established in the community communication platform, a residential area communication interface and a single-family communication platform will be established in the residential area communication platform, a single-family communication interface will be established in the single-family communication platform, and the communication content will be recorded. After the house transaction is completed, the transaction users will be visited to obtain useful information in the user's artificial communication content, and influence weights will be formulated for each segment of useful information by the user, and reward units will be formulated at the same time. The influence weights and useful information will be used to calculate the reward information of different members in the community communication interface, the residential area communication interface and the single-family communication interface.

[0046] By adopting the above technical solution, compared with the prior art, the beneficial effects of the present invention are:

[0047] 1. The present invention can provide users with a rich selection of houses through the house source integration module, greatly improving the efficiency of house hunting. The travel index analysis module can determine the travel index according to the travel information of the residential area, helping users understand the traffic convenience around the house, and providing an important reference for users with high travel needs. The housing area quality analysis module can determine the housing area quality according to the environment of the residential area and calculate the environmental index, so that users can fully consider the living environment factors when choosing a house, improve the living satisfaction, and use the intra-area communication module to promote communication and interaction between neighbors, enhance community cohesion, and enable users to understand the advantages and disadvantages of the house in more detail.

[0048] 2. The present invention can facilitate them to intuitively view various information through the housing source integration module, improve work efficiency and operational convenience, and help strengthen the supervision of the real estate market. The travel index analysis module can more scientifically evaluate the traffic capacity of roads around residential areas, provide an accurate basis for judging travel conditions, make the calculation of travel index more comprehensive and personalized, and better reflect the actual travel situation of residential areas, providing users with more valuable references when choosing houses, helping them to weigh traffic convenience and living needs;

[0049] 3. The present invention can provide important reference for home buyers and renters through the housing area quality analysis module, which helps them choose a more comfortable and healthy living environment, accurately reflects the impact of various aspects of the residential area on the overall environmental quality, and makes the evaluation results more reliable. The authority granting module can ensure that each user can only access information related to his or her responsibilities in the system. The intra-district communication module can encourage residents to actively participate in exchanges and share valuable information, while also providing a basis for improving community services and management. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 Schematic diagram of the system flow in an embodiment of the present invention. DETAILED DESCRIPTION

[0051] The specific embodiments of the present invention will be further described below in conjunction with the accompanying drawings. It should be noted that the description of these embodiments is used to help understand the present invention, but does not constitute a limitation of the present invention.

[0052] In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0053] Embodiment 1:

[0054] Therefore, in order to effectively solve the above problems, the present application proposes a house purchasing system based on big data, as shown in the accompanying drawings of the specification. Figure 1 As shown, it includes a login module, which is used to register an account for a user, and also includes a category analysis module, an authority granting module, an intra-district communication module, a housing source integration module, a travel index analysis module, and a housing area quality analysis module;

[0055] The housing source integration module collects housing information and divides it into communities, then integrates the first-hand housing real estate companies and second-hand housing real estate agencies in each community, obtains the housing source information of the first-hand housing real estate companies and second-hand housing real estate agencies in each community, generates housing information, and shares the housing source information with the corresponding communities;

[0056] Cooperate with local government real estate registration departments, property management companies, etc. to obtain more comprehensive and accurate basic information about the house, including the building year, ownership status, and maintenance records;

[0057] The travel index analysis module can extract house information, divide it into residential areas, obtain residential area information, and collect its travel information to determine the travel index;

[0058] Combined with the data from the intelligent transportation system, using the traffic flow monitored by intersection cameras and the real-time operation data of buses and subways, the travel index of residential communities can be more accurately determined;

[0059] Housing area quality analysis module, extracts residential area information, judges housing area quality according to the environment of the residential area, and calculates the housing area environment index;

[0060] Category analysis module, establishes second-hand housing units, rental housing units and new housing units, and users select housing purchase categories through second-hand housing units, rental housing units and new housing units, and obtain housing purchase location information;

[0061] The permission granting module establishes permission granting units, extracts user accounts, divides user accounts, obtains decentralized accounts, grants permissions to different decentralized accounts, and develops viewing panels for different permission types;

[0062] Segment users based on their occupation, identity background and other factors. For real estate investors, they are given specific investment analysis permissions to view more detailed real estate market trends and investment return analysis data; for real estate researchers, professional data analysis tools and research report access rights are provided;

[0063] The intra-district communication module extracts housing information and then divides the housing information into communities, residential areas and single-family houses, thereby generating community areas, residential area areas and single-family house areas respectively, and establishing a communication platform for them;

[0064] It also includes a trading platform module and a process display module;

[0065] The trading platform module extracts house information, establishes a trading platform, divides house information according to the type of permissions, and then publishes the divided house information to the corresponding viewing panel;

[0066] The process display module can establish a general backend processing unit, and establish national panels, provincial panels and city panel maps inside the main station processing unit, and establish city sections inside the city panel map. The homepage of the general backend processing unit can clearly view the number of stores in each province across the country and the location of stores in the current city map. Click the provincial panel to see the number of stores in each city in the current province. Click the city panel map to enter the city section. The city section displays the housing information of the current city and sets color difference labels for the housing information. The housing number, store data and housing data are recorded in blue, light blue and yellow labels respectively. When the mouse is placed on the blue, light blue and yellow points, the housing number, store data and housing data can be directly viewed;

[0067] Specific workflow: register an account, collect housing information, and divide it by community, integrate the first-hand housing real estate companies and second-hand housing real estate agencies in each community, obtain housing information, generate housing information, and share the housing information with the corresponding community, divide the housing information according to the residential area, obtain the residential area information, judge the travel index of the residential area, judge the quality of the residential area according to the environment of the residential area, calculate the housing area environment index, select the type of housing through the second-hand housing unit, rental unit and new housing unit, and obtain the housing location information, establish the authority granting unit, divide the user account, obtain the decentralized account, and grant different decentralized accounts. The account permissions are used to divide the housing information according to the community, residential area and single-family house, so as to generate community areas, residential area areas and single-family house areas respectively, and establish a communication platform for them, publish the divided housing information to the corresponding viewing panel, establish a general backend processing unit, and establish a national panel, provincial panel and city panel map inside the general station processing unit, establish a city section inside the city panel map, record the house number, store data and house data in the blue, light blue and yellow labels respectively, and when the mouse is placed on the blue, light blue and yellow points, the house number, store data and house data can be directly viewed;

[0068] Furthermore, the housing integration module can provide users with a rich selection of houses, greatly improving the efficiency of house hunting. The travel index analysis module can determine the travel index based on the travel information of the residential area, helping users understand the traffic convenience around the house, and providing important reference for users with high travel needs. The housing area quality analysis module can determine the quality of the residential area and calculate the environmental index based on the environment of the residential area, allowing users to fully consider the living environment factors when choosing a house and improve their living satisfaction. The intra-district communication module can promote communication and interaction between neighbors, enhance community cohesion, and enable users to understand the advantages and disadvantages of the house in more detail.

[0069] Embodiment 2:

[0070] Based on the first embodiment, as shown in the accompanying drawings of the specification Figure 1 As shown, after the house source integration module shares the house source information with the corresponding community, it will simultaneously establish a multi-layer architecture, where the multi-layer architecture includes a front-end display layer, a business logic layer, and a data storage layer;

[0071] The front-end display layer can provide a friendly user interface for housing management office staff to view various information;

[0072] According to the daily operation habits and focus of the housing management staff, relevant key information and hot housing data are automatically pushed. When the staff frequently checks the second-hand housing information in a certain area recently, the front-end display layer will give priority to displaying the latest second-hand housing dynamics in the area when logging in next time, and provide relevant market analysis briefings, including the second-hand housing price trend and supply and demand change trend in the area;

[0073] Business logic layer, which handles business operations such as data query, statistics, and audit;

[0074] The data storage layer is used to store information about real estate companies for first-hand housing, real estate agency companies for second-hand housing, and housing information;

[0075] The integrated first-hand real estate companies and second-hand real estate intermediary companies must be registered with the housing management office within the jurisdiction. The housing management office can view the information of the integrated first-hand real estate companies and second-hand real estate intermediary companies in the county through the system, the information of the houses currently being sold by each company, and the information of the houses that have been sold in the past;

[0076] After obtaining the residential area information, the travel index analysis module will extract the area information of the residential area and the actual road width information surrounding the residential area, and calculate the road width data that does not affect the traffic of residents in the residential area. The standard of the number of traffic per hour on the surrounding roads is T 标准 , assuming that the number of vehicles passing through per hour during peak hours is M 通行 , assuming the traffic efficiency of the road is T效率 , let the road width threshold be D 阈值 , assuming the ideal width of the road is D 理想 ;

[0077]

[0078] The above formula can be used to calculate the ideal width of the road, and at the same time, a road width threshold is established to limit the actual maximum road width. Suppose the road width threshold is D 阈值 , let the determined road width be D 判定 ;

[0079] When D 理想 >D 阈值 When the road width is determined, the road width threshold is used as the main factor. 阈值 It will cover D 判定 ;

[0080] When D 理想 ≤D 阈值 When the ideal width of the road is used as the main factor to determine the road width, D 理想 It will cover D 判定 ;

[0081] According to the above method, the road width can be determined;

[0082] Allow users to customize and adjust the weight of the information in the factor expansion unit according to their travel habits and preferences. For users who often use shared bicycles, the weight of the shared bicycle factor can be set higher. When calculating the travel index, the system will focus more on the travel mode that the user is concerned about, and provide a travel index reference that is more in line with personal needs. The system can continuously optimize the personalized travel index model based on the user's historical travel data and feedback information to improve the accuracy and practicality of the calculation results;

[0083] After the travel index analysis module obtains the determined road width, it also needs to calculate the ratio of the actual road width to the determined width, and comprehensively consider factors such as public transportation, shared travel tools, travel time cost, and proximity to transportation hubs. Users can add factors to expand the information in the unit as needed to calculate the travel index of the residential area. Suppose the actual road width information is D 实际 , let the travel index be C Z , let the impact of the factor on the travel index be C Y , let the number of factors be M;

[0084]

[0085] According to the above formula, the travel index of the residential area can be calculated;

[0086] Specific workflow: Establish a multi-layer framework, which includes a front-end display layer, a business logic layer, and a data storage layer. The front-end display layer can provide a friendly user interface for housing management staff to view various types of information. The business logic layer handles data query, statistics, and audit operations. The data storage layer is used to store information about first-hand real estate companies, second-hand real estate agency companies, and housing sources. It extracts the floor area information of residential areas and the actual road width information surrounding residential areas, calculates the road width data that does not affect the traffic of residents in the residential area, calculates the ideal width of the road, and establishes a road width threshold. When D 理想 >D 阈值 When the road width is determined, the road width threshold is used as the main factor. 阈值 It will cover D 判定 , when D 理想 ≤D 阈值 When the ideal width of the road is used as the main factor to determine the road width, D 理想 It will cover D 判定 , the determined road width is obtained, and a factor expansion unit is established. The user can supplement the information in the factor expansion unit as needed to calculate the travel index of the residential area;

[0087] Furthermore, the housing integration module can facilitate them to intuitively view various types of information, improve work efficiency and operational convenience, and help strengthen supervision of the real estate market. The travel index analysis module can more scientifically evaluate the traffic capacity of roads around residential areas, provide an accurate basis for judging travel conditions, and make the calculation of the travel index more comprehensive and personalized, which can better reflect the actual travel conditions in residential areas, provide users with more valuable references when choosing houses, and help them weigh transportation convenience and living needs.

[0088] Embodiment three:

[0089] Based on the second embodiment, as shown in the accompanying drawings of the specification Figure 1 As shown in the figure, after extracting the residential area information, the housing area quality analysis module will analyze the green coverage area information, plant diversity information, environmental sanitation information, building density information and imaging density information in the residential area information. Suppose the ideal green coverage rate is L 覆盖率 , let the vertical projection area of ​​the green area of ​​the residential area be J L , let the vertical projection area of ​​green space be S, let the floor area of ​​residential area be F 占地面积 , let the green coverage area index be L ZS ;

[0090]

[0091] Based on the above information, we can calculate the green coverage area index, plant diversity index, environmental sanitation index, building density index, image density index and advertising index. Let the number of advertisements not in the advertisement column be G. 数量 , let the number of solid surfaces in the residential area be L S , let the advertising index be G 指数 ;

[0092]

[0093] The advertising index can be calculated through the above formula;

[0094] After calculating the advertising index, the housing area quality analysis module will set index weights for the green coverage area index, plant diversity index, environmental sanitation index, building density index, and contrast density index, and convert the green coverage area index, plant diversity index, environmental sanitation index, building density index, and contrast density index into different factor indexes. Let the factor index be Y Z , let the number of factors be B, let the weights of different factor indexes be Z Q , let the housing area environment index be F 环境指数 , let the influence weight of advertising index be G 权重 ;

[0095]

[0096] According to the above formula, the housing area environment index can be calculated, where

[0097] Connect with the monitoring system of the environmental protection department to obtain real-time air quality indicators, water quality and noise levels around residential areas, and incorporate these data into the housing area environmental quality assessment system to more comprehensively reflect the comprehensive quality of the living environment;

[0098] After obtaining the location information of the house, the category analysis module will formulate a viewing interface according to the second-hand housing unit, rental unit and new housing unit, and generate a multi-layer interface. After dividing the user account, the permission granting module will obtain the general backend account, direct store account, store account, community account, housing management office account, urban management account and bank account;

[0099] The general backend account has the authority to view all second-hand housing location information, new housing location information, rental location information, small advertisement location information, salesperson location information, housekeeping staff location information and store location information across the country;

[0100] The permissions of the direct-sale store account can see all the second-hand housing location information, new housing location information, rental location information, small advertisement location information, salesperson location information, housekeeping staff location information and store location information across the country;

[0101] The store account has the authority to view the location information of the salesperson bound to the store, the location information of the second-hand houses, new houses, and rental houses managed by the store, the current location information of the store, and the city-level information of the current city;

[0102] The community account has the authority to view the second-hand housing location information, new housing location information, rental housing location information, and electronic advertising location information within the district or county;

[0103] The account of the Housing Management Office has the authority to view the location information of second-hand houses, new houses, rental houses, salespersons and stores within the district or county.

[0104] The permissions of the urban management account can see the location information of small advertisements within the district or county;

[0105] The bank account permissions allow you to see the second-hand housing location information, new housing location information, and rental housing location information within your own district or county;

[0106] Dynamically adjust the account based on factors such as the user's credit rating and business activity. For real estate agency accounts with good credit and long-term activity, grant certain permissions to expand the account so that it can view more housing information in surrounding areas to promote its business development. For user accounts that violate regulations or have poor credit, reduce their permissions or take restrictive measures accordingly;

[0107] After the intra-district communication module generates community areas, residential areas and single-family areas, it will develop a community communication platform for the community area, establish a community communication interface and a residential area communication platform in the community communication platform, establish a residential area communication interface and a single-family communication platform in the residential area communication platform, and establish a single-family communication interface in the single-family communication platform, and record the communication content. After the house transaction is completed, it will visit the transaction users to obtain useful information in the user's artificial communication content, and formulate influence weights for each useful information segment through the user, and formulate reward units at the same time, and then use the influence weights and useful information to calculate the reward information of different members in the community communication interface, residential area communication interface and single-family communication interface;

[0108] Specific workflow: Analyze the green coverage area information, plant diversity information, environmental sanitation information, building density information and imaging density information in the residential area information, calculate the green coverage area index, plant diversity index, environmental sanitation index, building density index, imaging density index and advertising index, set index weights for the green coverage area index, plant diversity index, environmental sanitation index, building density index and imaging density index, calculate the housing area environment index, generate a multi-layer interface, obtain the total backend account, direct store account, store account, community account, housing management office account, urban management account and bank account, and set different permissions for them, formulate a community communication platform for the community area, establish a community communication interface and a residential community communication platform in the community communication platform, establish a residential community communication interface and a single-family communication platform in the residential community communication platform, establish a single-family communication interface in the single-family communication platform, and record the communication content, formulate a reward unit, and then use the influence weight and useful information to calculate the reward information of different members in the community communication interface, the residential community communication interface and the single-family communication interface;

[0109] Furthermore, the housing area quality analysis module can provide important reference for home buyers and renters, help them choose a more comfortable and healthy living environment, accurately reflect the impact of various aspects of the residential area on the overall environmental quality, and make the evaluation results more reliable. The authority granting module can ensure that each user can only access information related to his or her responsibilities in the system. The intra-district communication module can encourage residents to actively participate in exchanges and share valuable information, while also providing a basis for improving community services and management.

[0110] The above shows and describes the basic principles, main features and advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A house purchasing system based on big data, comprising a login module, wherein the login module is used to register an account for a user, and wherein: It also includes a category analysis module, a permission granting module, an intra-district communication module, a housing source integration module, a travel index analysis module, and a housing district quality analysis module; The housing source integration module collects housing information and divides it into communities, then integrates the first-hand housing real estate companies and second-hand housing real estate agencies in each community, obtains the housing source information of the first-hand housing real estate companies and second-hand housing real estate agencies in each community, generates housing information, and shares the housing source information with the corresponding communities; The travel index analysis module can extract house information, divide it into residential areas, obtain residential area information, and collect its travel information to determine the travel index; Housing area quality analysis module, extracts residential area information, judges housing area quality according to the environment of the residential area, and calculates the housing area environment index; Category analysis module, establishes second-hand housing units, rental housing units and new housing units, and users select housing purchase categories through second-hand housing units, rental housing units and new housing units, and obtain housing purchase location information; The permission granting module establishes permission granting units, extracts user accounts, divides user accounts, obtains decentralized accounts, grants permissions to different decentralized accounts, and develops viewing panels for different permission types; The intra-district communication module extracts housing information and then divides the housing information into communities, residential areas and single-family houses, thereby generating community areas, residential area areas and single-family house areas respectively, and establishing a communication platform for them.

2. A house purchasing system based on big data according to claim 1, characterized in that: It also includes a trading platform module and a process display module; The trading platform module extracts house information, establishes a trading platform, divides house information according to the type of permissions, and then publishes the divided house information to the corresponding viewing panel; The process display module can establish a general background processing unit, and establish national panel, provincial panel and city panel maps inside the main station processing unit, and establish city sections inside the city panel map. The homepage of the general background processing unit can clearly view the number of stores in each province across the country and the location of the stores in the current city map. Click the provincial panel to see the number of stores in each city in the current province. Click the city panel map to enter the city section. The city section displays the housing information of the current city and sets color difference labels for the housing information. The housing number, store data and housing data are recorded in blue, light blue and yellow labels respectively. When the mouse is placed on the blue, light blue and yellow dots, the housing number, store data and housing data can be directly viewed.

3. The housing purchase system based on big data according to claim 1, characterized in that: After the housing source integration module shares the housing source information with the corresponding community, it will simultaneously establish a multi-layer architecture, wherein the multi-layer architecture includes a front-end display layer, a business logic layer and a data storage layer; The front-end display layer can provide a friendly user interface for housing management office staff to view various information; Business logic layer, which handles business operations such as data query, statistics, and audit; The data storage layer is used to store information about real estate companies for first-hand housing, real estate agency companies for second-hand housing, and housing information; The integrated first-hand real estate companies and second-hand real estate agencies must be registered with the housing management office within the jurisdiction. The housing management office can view the integrated first-hand real estate company information, second-hand real estate agency information, the current housing information of each company, and the housing information that has been sold in the past through the system.

4. The housing purchase system based on big data according to claim 1, characterized in that: After obtaining the residential area information, the travel index analysis module will extract the area information of the residential area and the actual road width information surrounding the residential area, and calculate the road width data that does not affect the traffic of residents in the residential area. The standard of the number of traffic per hour on the surrounding roads is T 标准 , assuming that the number of vehicles passing through per hour during peak hours is M 通行 , assuming the traffic efficiency of the road is T 效率 , let the road width threshold be D 阈值 , assuming the ideal width of the road is D 理想 ; The above formula can be used to calculate the ideal width of the road, and at the same time, a road width threshold is established to limit the actual maximum road width. Suppose the road width threshold is D 阈值 , let the determined road width be D 判定 ; When D 理想 >D 阈值 When the road width is determined, the road width threshold is used as the main factor. 阈值 It will cover D 判定 ; When D 理想 ≤D 阈值 When the ideal width of the road is used as the main factor to determine the road width, D 理想 It will cover D 判定 ; The road width can be determined according to the above method.

5. A house purchasing system based on big data according to claim 4, characterized in that: After obtaining the determined road width, the travel index analysis module needs to calculate the ratio of the actual road width to the determined width, and comprehensively consider factors such as public transportation, shared travel tools, travel time cost, and proximity to transportation hubs. Users can add factors to expand the information in the unit as needed to calculate the travel index of the residential area. Suppose the actual road width information is D 实际 , let the travel index be C Z , let the impact of the factor on the travel index be C Y , let the number of factors be M; The travel index of the residential area can be calculated according to the above formula.

6. The housing purchase system based on big data according to claim 1, characterized in that: After extracting the residential area information, the housing area quality analysis module will analyze the green coverage area information, plant diversity information, environmental sanitation information, building density information and imaging density information in the residential area information. The ideal green coverage rate is L 覆盖率 , let the vertical projection area of ​​the green area of ​​the residential area be J L , let the vertical projection area of ​​green space be S, let the floor area of ​​residential area be F 占地面积 , let the green coverage area index be L ZS ; Based on the above information, we can calculate the green coverage area index, plant diversity index, environmental sanitation index, building density index, image density index and advertising index. Let the number of advertisements not in the advertisement column be G. 数量 , let the number of solid surfaces in the residential area be L S , let the advertising index be G 指数 ; The advertising index can be calculated using the above formula.

7. A house purchasing system based on big data according to claim 6, characterized in that: After calculating the advertising index, the housing area quality analysis module sets index weights for the green coverage area index, plant diversity index, environmental sanitation index, building density index, and contrast density index, and converts the index weights for the green coverage area index, plant diversity index, environmental sanitation index, building density index, and contrast density index into different factor indexes. Let the factor index be Y Z , let the number of factors be B, let the weights of different factor indexes be Z Q , let the housing area environment index be F 环境指数 , let the influence weight of advertising index be G 权重 ; According to the above formula, the housing area environment index can be calculated, where 8. The housing purchase system based on big data according to claim 1, characterized in that: After obtaining the location information of the house, the category analysis module will formulate a viewing interface according to the second-hand housing unit, the rental unit and the new housing unit to generate a multi-layer interface. After dividing the user account, the permission granting module will obtain the general backend account, the direct store account, the store account, the community account, the housing management office account, the urban management account and the bank account; The general backend account has the authority to view all second-hand housing location information, new housing location information, rental location information, small advertisement location information, salesperson location information, housekeeping staff location information and store location information across the country; The permissions of the direct-sale store account can see all the second-hand housing location information, new housing location information, rental location information, small advertisement location information, salesperson location information, housekeeping staff location information and store location information across the country; The store account has the authority to view the location information of the salesperson bound to the store, the location information of the second-hand houses, new houses, and rental houses managed by the store, the current location information of the store, and the city-level information of the current city; The community account has the authority to view the second-hand housing location information, new housing location information, rental housing location information, and electronic advertising location information within the district or county; The account of the Housing Management Office has the authority to view the location information of second-hand houses, new houses, rental houses, salespersons and stores within the district or county. The permissions of the urban management account can see the location information of small advertisements within the district or county; The bank account permissions allow you to view the location information of second-hand houses, new houses, and rental houses within your district or county.

9. The housing purchase system based on big data according to claim 1, characterized in that: After the intra-district communication module generates the community area, the residential area and the single-family area, it will develop a community communication platform for the community area, establish a community communication interface and a residential area communication platform in the community communication platform, establish a residential area communication interface and a single-family communication platform in the residential area communication platform, establish a single-family communication interface in the single-family communication platform, and record the communication content. After completing the house transaction, it will visit the transaction users to obtain useful information in the user's artificial communication content, and formulate influence weights for each segment of useful information through the users, and formulate reward units at the same time, and then use the influence weights and useful information to calculate the reward information of different members in the community communication interface, the residential area communication interface and the single-family communication interface.

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