House resource data processing method and device, electronic equipment and medium

Abstract

The invention relates to the technical field of image processing, and provides a housing resource data processing method and device, electronic equipment and a medium. The method comprises the following steps: acquiring housing resource data of a to-be-evaluated housing resource and housing resource data of a reference housing resource; according to the housing resource data of the to-be-assessed housing resource, determining the housing resource index flow rate of the to-be-assessed housing resource and the housing resource index increase of the to-be-assessed housing resource; according to the housing resource data of the reference housing resource, determining the housing resource index flow rate of the reference housing resource and the housing resource index increase of the reference housing resource; according to the housing resource index flow velocity of the to-be-evaluated housing resource, determining the housing resource grade of the to-be-evaluated housing resource; and according to the housing resource grade of the housing resource to be evaluated, the housing resource index increase of the housing resource to be evaluated and the housing resource index increase of the reference housing resource, determining the label data of the current competitiveness of the housing resource to be evaluated. According to the invention, the problems of low efficiency and insufficient accuracy in the data acquisition and labeling process in the real estate field in the prior art are solved.

Description

Technical Field

[0001] The present disclosure relates to the technical field of house data processing, and in particular to a house data processing method, device, electronic equipment and medium. Background Art

[0002] With the rapid development of Internet technology, the application of big data in all walks of life has become increasingly popular, providing strong support for solving problems in specific fields. In the real estate field, it has become a common practice to use a large amount of housing data to formulate project strategies. However, there are some challenges in the current data acquisition and processing methods, especially in the process of obtaining label data, which is inefficient and inaccurate. The current practice is to manually collect housing data, analyze and calculate, and then manually label different labels according to the calculation results. This method has the following problems: Manual collection and labeling of data is time-consuming and labor-intensive, and cannot meet the needs of large-scale data processing, resulting in inefficient data acquisition process. Manual labeling is prone to subjective judgment and errors, resulting in insufficient accuracy of label data, affecting the formulation and optimization of subsequent recommendation strategies. Summary of the invention

[0003] In view of this, the embodiments of the present disclosure provide an image processing method, device, electronic device and computer-readable storage medium to solve the technical problems of low efficiency and accuracy in obtaining label data in the prior art.

[0004] According to a first aspect of an embodiment of the present disclosure, a housing data processing method is provided, including: obtaining housing data of a housing to be evaluated and housing data of a reference housing; determining a housing index flow rate of the housing to be evaluated and an increase in housing index of the housing to be evaluated based on the housing data of the housing to be evaluated; determining a housing index flow rate of the reference housing and an increase in housing index of the reference housing based on the housing data of the reference housing; determining a housing grade of the housing to be evaluated based on the housing index flow rate of the housing to be evaluated; determining label data of the current competitiveness of the housing to be evaluated based on the housing grade of the housing to be evaluated, the increase in housing index of the housing to be evaluated and the increase in housing index of the reference housing.

[0005] According to a second aspect of an embodiment of the present disclosure, a housing data processing device is provided, comprising: an acquisition module for acquiring housing data of a housing source to be evaluated and housing data of a reference housing source; a first determination module for determining the housing index flow rate of the housing source to be evaluated and the housing index increase rate of the housing source to be evaluated based on the housing data of the housing source to be evaluated; a second determination module for determining the housing index flow rate of the reference housing source and the housing index increase rate of the reference housing source based on the housing data of the reference housing source; a third determination module for determining the housing grade of the housing source to be evaluated based on the housing index flow rate of the housing source to be evaluated; and a fourth determination module for determining label data of the current competitiveness of the housing source to be evaluated based on the housing grade of the housing source to be evaluated, the housing index increase rate of the housing source to be evaluated, and the housing index increase rate of the reference housing source.

[0006] According to a third aspect of an embodiment of the present disclosure, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above method when executing the computer program.

[0007] According to a fourth aspect of the embodiments of the present disclosure, a computer-readable storage medium is provided, which stores a computer program, and when the computer program is executed by a processor, the steps of the above method are implemented.

[0008] Compared with the prior art, the embodiments of the present disclosure have the following beneficial effects: the embodiments of the present disclosure can automatically obtain the housing data of the housing source to be evaluated and the reference housing source, and calculate the housing source index flow rate and housing source index increase rate based on these data, thereby realizing automation and efficiency of data processing. Compared with the manual method, this automated method greatly improves the efficiency of data processing, saving time and labor costs. By determining the housing source level according to the housing source index flow rate and housing source index increase rate, and determining the current competitiveness label of the housing source to be evaluated in combination with the data of the reference housing source, the present invention considers more factors when annotating the label data, reduces subjective errors, and improves the accuracy and reliability of the label data. By determining the current competitiveness label of the housing source to be evaluated, more accurate data support is provided for the formulation of subsequent recommendation strategies. Based on more accurate label data, the recommendation strategy of the terminal device can be optimized to improve user experience and recommendation accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0010] Figure 1A schematic diagram showing an exemplary system architecture to which the technical solution of an embodiment of the present invention can be applied;

[0011] Figure 2 It is a flowchart of a housing data processing method provided by an embodiment of the present disclosure;

[0012] Figure 3 is a schematic diagram of the mapping between the increase and the label data provided by the embodiment of the present disclosure;

[0013] Figure 4 is a block diagram of a housing data processing device provided by an embodiment of the present disclosure;

[0014] Figure 5 It is a structural schematic diagram of an electronic device provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0015] In the following description, specific details such as specific system structures and technologies are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present disclosure. However, it should be clear to those skilled in the art that the present disclosure may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid obstructing the description of the present disclosure with unnecessary details.

[0016] It should be noted that the user information (including but not limited to terminal device information, user personal information, etc.) and data (including but not limited to data for display, data for analysis, etc.) involved in this disclosure are all information and data authorized by the user or fully authorized by all parties.

[0017] Figure 1 A schematic diagram showing an exemplary system architecture to which the technical solution of an embodiment of the present invention can be applied.

[0018] like Figure 1 As shown, the system architecture 100 may include one or more of a first terminal device 101, a second terminal device 102, and a third terminal device 103, a network 104, and a server 105. The network 104 is used to provide a medium for a communication link between the first terminal device 101, the second terminal device 102, the third terminal device 103, and the server 105. The network 104 may include various connection types, such as wired, wireless communication links, or optical fiber cables, etc.

[0019] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration. According to the implementation requirements, there may be any number of terminal devices, networks and servers. For example, the server 105 may be a server cluster composed of multiple servers.

[0020] The user can use the first terminal device 101, the second terminal device 102, and the third terminal device 103 to interact with the server 105 through the network 104 to receive or send data, etc. The first terminal device 101, the second terminal device 102, and the third terminal device 103 can be various electronic devices with display screens, including but not limited to smart phones, tablet computers, portable computers, desktop computers, and the like.

[0021] The server 105 may be a server that provides various services. For example, the server 105 may obtain the housing source data of the housing source to be evaluated and the housing source data of the reference housing source from the first terminal device 103 (which may also be the second terminal device 102 or the third terminal device 103); determine the housing source index flow rate of the housing source to be evaluated and the housing source index increase of the housing source to be evaluated according to the housing source data of the housing source to be evaluated; determine the housing source index flow rate of the reference housing source and the housing source index increase of the reference housing source according to the housing source data of the reference housing source; determine the housing source grade of the housing source to be evaluated according to the housing source index flow rate of the housing source to be evaluated; determine the label data of the current competitiveness of the housing source to be evaluated according to the housing source grade of the housing source to be evaluated, the housing source index increase of the housing source to be evaluated, and the housing source index increase of the reference housing source.

[0022] In some embodiments, the image processing method provided by the embodiment of the present invention is generally executed by the server 105, and accordingly, the image processing device is generally set in the server 105. In other embodiments, some terminal devices may have functions similar to those of the server to execute the method. Therefore, the image processing method provided by the embodiment of the present invention is not limited to being executed on the server side.

[0023] The image processing method and device according to the embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings.

[0024] Figure 2 is a flowchart of a method for processing house data provided by an embodiment of the present disclosure. The method provided by an embodiment of the present disclosure can be executed by any electronic device with computer processing capabilities, for example, the electronic device can be Figure 1 The server is shown.

[0025] like Figure 2 As shown, the housing data processing method includes steps S210 to S250.

[0026] In step S210, the property data of the property to be evaluated and the property data of the reference property are obtained.

[0027] Step S220, determining the housing source index flow rate and the housing source index increase rate of the housing source to be evaluated according to the housing source data of the housing source to be evaluated.

[0028] In step S230, based on the house source data of the reference house source, the house source index flow rate of the reference house source and the house source index increase rate of the reference house source are determined.

[0029] In step S240, the housing source grade of the housing source to be evaluated is determined according to the housing source index flow rate of the housing source to be evaluated.

[0030] In step S250, label data of the current competitiveness of the house to be evaluated is determined based on the house grade of the house to be evaluated, the increase in the house index of the house to be evaluated, and the increase in the house index of the reference house.

[0031] The method can realize automation and efficiency of data processing by automatically acquiring the housing data of the housing source to be evaluated and the reference housing source, and calculating the housing source index flow rate and housing source index increase based on these data. Compared with the manual method, this automated method greatly improves the data processing efficiency and saves time and labor costs. By determining the housing source level according to the housing source index flow rate and housing source index increase, and combining the data of the reference housing source to determine the current competitiveness label of the housing source to be evaluated, the present invention considers more factors when annotating the label data, reduces subjective errors, and improves the accuracy and reliability of the label data. By determining the current competitiveness label of the housing source to be evaluated, more accurate data support is provided for the formulation of subsequent recommendation strategies. Based on more accurate label data, the recommendation strategy of the terminal device can be optimized to improve user experience and recommendation accuracy.

[0032] In some embodiments of the present disclosure, the housing source to be evaluated may refer to a building or property to be evaluated. These housing source data are used to evaluate the competitiveness and performance of the building or property in the market. The housing source data of the housing source to be evaluated may cover multiple historical periods, each of which represents a specific time span. The settings of these historical periods can be adjusted according to actual conditions and needs to adapt to different market conditions and analysis requirements. The housing source data of the housing source to be evaluated in each historical period contains various attribute indicators to describe the performance of the building or property during the time period. Among them, the attribute indicators may include but are not limited to: Number of subscribed houses: indicates the number of houses subscribed to the building in each period. This indicator can reflect the market demand and popularity of the building, and is one of the important reference indicators for evaluating the competitiveness of housing sources. By analyzing the changes in these attribute indicators in different historical periods, the development trend and market performance of the housing source to be evaluated can be more comprehensively understood, providing strong support for subsequent competitiveness evaluation and recommendation strategy formulation.

[0033] In some embodiments of the present disclosure, the reference housing source may refer to a competing building or property, which is used as a reference object for the housing source to be evaluated. By analyzing the data of the reference housing source, the performance and competitiveness of the housing source to be evaluated in the market can be more comprehensively evaluated. The housing source data of the reference housing source can also cover multiple historical periods, each historical period representing a specific time span. The settings of these historical periods can be adjusted according to actual conditions and needs to ensure the comprehensiveness and accuracy of the analysis data. The housing source data of the reference housing source in each historical period contains various attribute indicators to describe the performance of the competing building or property during the time period. Among them, the attribute indicators may include but are not limited to: Number of subscribed houses: indicates the number of houses subscribed to the competing building in each period. This indicator can help compare the differences in market recognition and sales between the housing source to be evaluated and the competing housing source, and provide an important reference for competitiveness evaluation.

[0034] In some embodiments of the present disclosure, determining the housing index flow rate and the housing index increase rate of the housing source to be evaluated based on the housing data of the housing source to be evaluated includes: calculating the housing index flow rate of the housing source to be evaluated based on the number of time periods corresponding to the housing data of the housing source to be evaluated and the attribute indicators in the housing data of the housing source to be evaluated each week; calculating the housing index increase rate of the housing source to be evaluated based on the number of time periods corresponding to the housing data of the housing source to be evaluated, the attribute indicators in the housing data of the housing source to be evaluated each week, and the sum of the attribute indicators in the housing data of the housing source to be evaluated.

[0035] Based on the above embodiment, the flow rate of the house source index of the house source to be evaluated is calculated according to the number of time periods corresponding to the house source data of the house source to be evaluated and the attribute index in the house source data of the house source to be evaluated each week. Specifically, the flow rate x of the house source index of the house source to be evaluated can be calculated by the following formula:

[0036]

[0037] Among them, n is the number of time periods corresponding to the listing data of the listings to be evaluated, and w is the attribute index in the listing data of the listings to be evaluated each week. This formula can accurately calculate the number of houses subscribed in multiple historical periods of the listings to be evaluated.

[0038] Based on the above embodiment, taking n as 4 as an example, the increase in the index of the house to be evaluated is calculated according to the number of time periods corresponding to the house data of the house to be evaluated, the attribute index in the house data of the house to be evaluated each week, and the sum of the attribute index in the house data of the house to be evaluated. The increase in the index of the house to be evaluated, y, can be calculated by the following formula:

[0039]

[0040] Among them, n is the number of time periods corresponding to the listing data of the listings to be evaluated, and w is the attribute index in the listing data of the listings to be evaluated each week. W4 is the attribute index in the listing data of the listings to be evaluated in the fourth week, that is, the number of houses subscribed in the fourth period. The increase in the listing index of the four historical periods can be calculated through this formula.

[0041] In some embodiments of the present disclosure, determining the housing source index flow rate and the housing source index increase rate of the reference housing source based on the housing source data of the reference housing source includes: calculating the housing source index flow rate of the reference housing source based on the number of time periods corresponding to the housing source data of the reference housing source and the attribute indicators in the housing source data of the reference housing source in each period; calculating the housing source index increase rate of the housing source to be evaluated based on the number of time periods corresponding to the housing source data of the reference housing source, the attribute indicators in the housing source data of the reference housing source in each period, and the sum of the attribute indicators in the housing source data of the reference housing source. The housing source index flow rate of the reference housing source can be calculated according to the above formula for calculating the housing source index flow rate of the housing source to be evaluated, which will not be repeated here. The housing source index increase rate of the reference housing source can be calculated according to the above formula for calculating the housing source index increase rate of the housing source to be evaluated.

[0042] The above formula can be used to calculate the housing source index flow rate and housing source index increase rate corresponding to the housing source to be evaluated and the reference housing source. The housing source to be evaluated can be graded by analyzing the housing source index flow rate of the housing source to be evaluated. For example, according to the housing source index flow rate of the housing source to be evaluated, determining the housing source grade of the housing source to be evaluated includes: when the housing source index flow rate of the housing source to be evaluated is greater than or equal to the first flow rate threshold, determining that the housing source grade of the housing source to be evaluated is a high-level housing source; when the housing source index flow rate of the housing source to be evaluated is greater than or equal to the second flow rate threshold and less than the first flow rate threshold, determining that the housing source grade of the housing source to be evaluated is a medium-level housing source; when the housing source index flow rate of the housing source to be evaluated is less than the second flow rate threshold, determining that the housing source grade of the housing source to be evaluated is a low-level housing source. In this embodiment, the first flow rate threshold can be set to 50, and the second flow rate threshold can be set to 30. The high-level housing source can be a traffic housing source, that is, a housing source with a high number of subscriptions, and the medium-level housing source can be an ordinary housing source, that is, a housing source with a moderate number of subscriptions. Low-level housing sources may be more difficult housing sources, i.e., housing sources with a smaller number of subscriptions. By determining the housing source level of the housing source to be evaluated, it can help users to more quickly understand the performance of the housing source in terms of the number of subscriptions, so as to better formulate corresponding marketing strategies and promotion plans. This classification of housing source levels can provide an important reference basis for real estate market analysis and decision-making, and help users better understand the market positioning and competition of different housing sources. Through the above description, this embodiment will determine the level of the housing source according to the housing source indicator flow rate of the housing source to be evaluated, and divide it into high-level housing sources, medium-level housing sources and low-level housing sources, so as to help users better understand the market position and competitiveness of the housing source.

[0043] In some embodiments of the present disclosure, the label data of the current competitiveness of the above-mentioned housing source to be evaluated can be rising opportunities, suggestions for observation, problem items, risk items, etc. The current competitiveness label of the housing source to be evaluated is determined based on the comprehensive performance and market potential of the housing source, and is used to guide decision makers in different classifications and treatment methods of the housing source. These labels reflect the competitive situation and development potential of the housing source in the current market environment. Specifically, rising opportunities: refers to the housing source to be evaluated has good market performance and development potential, and may have value-added space and development opportunities in the future. Suggested observation: refers to the housing source to be evaluated is in the observation stage in the market, and its market performance and development trend need to be further observed. Problem items: refers to the housing source to be evaluated has some problems or potential risks, which need to be focused on and handled to enhance competitiveness. Risk items: refers to the housing source to be evaluated has a high market risk, may face some unfavorable factors or challenges, and need to be carefully considered and handled. By adding current competitiveness label data to the housing source to be evaluated, it can help decision makers to have a more comprehensive understanding of the position and potential of the housing source in the market competition. These label data can provide important reference information for decision makers to help them formulate market strategies and management plans for different types of housing sources. According to different competitiveness labels, decision makers can formulate marketing plans, pricing strategies, improvement plans, etc. in a targeted manner. This embodiment will add current competitiveness label data to the properties to be evaluated, providing decision makers with more comprehensive market analysis and decision support, helping them better grasp the real estate market dynamics and formulate corresponding strategies.

[0044] In some embodiments of the present disclosure, according to the housing source level of the housing source to be evaluated, the housing source index increase of the housing source to be evaluated, and the housing source index increase of the reference housing source, determining the label data of the current competitiveness of the housing source to be evaluated includes: according to the housing source level of the housing source to be evaluated, calling the label mapping table corresponding to the housing source level; determining the increase type of the housing source to be evaluated according to the housing source index increase of the housing source to be evaluated, and determining the increase type of the reference housing source according to the housing source index increase of the reference housing source; according to the increase type of the housing source to be evaluated, the increase type of the reference housing source and the label mapping table corresponding to the housing source level, determining the label data of the current competitiveness of the housing source to be evaluated. In this example, the increase type can be determined according to the size of the increase, for example, if the increase is greater than or equal to 50%, the increase type is defined as a big increase, if the increase is greater than 0% and less than 50%, the increase type is defined as an increase, if the increase is greater than or equal to -20% and less than 0%, the increase type is defined as a slight decrease, and if the increase is less than -20%, the increase type is defined as a decrease.

[0045] refer to Figure 3 , based on the comparison between the increase of the property index of the property data to be evaluated and the above increase threshold, the increase type can be divided into project big increase, project increase, project slight decrease, and project decrease. Similarly, the increase type of the reference property can be competitor's big increase, competitor's increase, competitor's slight decrease, and competitor's decrease.

[0046] Based on the above-mentioned embodiment, according to the price increase type of the house to be evaluated, the price increase type of the reference house, and the label mapping table corresponding to the house level, determining the label data of the current competitiveness of the house to be evaluated includes: traversing the label mapping table based on the price increase type of the house to be evaluated and the price increase type of the reference house to obtain the mapping relationship between the price increase type of the house to be evaluated and the price increase type of the reference house; and determining the label data of the current competitiveness of the house to be evaluated according to the mapping relationship. Figure 3 , taking the flow of the project to be evaluated of the property level of the property to be evaluated, that is, the high-level property, as an example, according to the mapping table, it can be determined that when the project rises sharply and the competing products rise sharply, the determined label data is red, and the red is defined as the property to be evaluated has a chance to rise. When the project rises and the competing products fall slightly, the determined label data is orange, and the orange is defined as the property to be evaluated is recommended for observation. When the project falls slightly and the competing products rise sharply, the determined label data is green, and the green is defined as the property to be evaluated is a problem project. When the project falls slightly and the competing products fall slightly, the determined label data is gray, and the gray is defined as a risky project. The method of determining the label data in the mapping table corresponding to other property levels is the same as the above method and will not be repeated here.

[0047] It should be noted that the increase type and label data can be configured in advance according to actual conditions and no limitation is made here.

[0048] In some embodiments of the present disclosure, the method further includes: generating a recommendation strategy for the housing source to be evaluated in the current cycle based on the label data of the current competitiveness of the housing source to be evaluated; and sending the recommendation strategy for the housing source to be evaluated in the current cycle to the terminal devices in the preset list. For example, according to the label data of the current competitiveness of the housing source to be evaluated, the corresponding recommendation strategy will be automatically generated. For example, for the housing source with the label of "rising opportunity", the recommendation strategy may include measures such as increasing marketing efforts and improving exposure; for the housing source with the label of "problem project" or "risk project", the recommendation strategy may include measures such as optimizing pricing and improving housing conditions. According to the label data and the preset strategy rules, the recommendation strategy for the housing source to be evaluated in the current cycle is automatically generated. These strategies will provide personalized recommendation solutions for each housing source based on the competitiveness and market potential of the housing source. The generated recommendation strategy for the housing source to be evaluated will be pushed to the terminal devices in the preset list, such as mobile phones, tablet computers, etc. The terminal device user will receive the pushed notification of the recommendation strategy for the housing source to be evaluated, and can view the detailed recommendation content and suggested measures. The terminal device user can make further decisions and executions based on the received recommendation strategy information. They can consider taking recommended marketing strategies, pricing adjustments, or other measures to improve the competitiveness and market performance of the properties to be evaluated. The system can collect user feedback and performance data on the recommended strategies to continuously optimize the recommendation algorithm and strategy generation process, and improve the accuracy and effectiveness of the recommendations. Through the above process, the system can automatically generate recommended strategies based on the current competitiveness label data of the properties to be evaluated, and send these strategies to the terminal devices in the preset list, providing users with personalized real estate market recommendations and decision support.

[0049] In some embodiments of the present disclosure, the house to be evaluated may be a real estate to be evaluated. The house source data of the house to be evaluated may be the house source data generated in multiple historical periods of the house to be evaluated. The historical period may be set according to actual conditions, and the house source data may include the number of time periods corresponding to the house source data of the house to be evaluated and the attribute index in the house source data of the house to be evaluated each week. The attribute index may indicate the number of houses subscribed to the real estate in each period.

[0050] Figure 4 It is a block diagram of a housing data processing device provided in an embodiment of the present disclosure.

[0051] like Figure 4 As shown, the housing data processing device 400 includes an acquisition module 410, a first determination module 420, a second determination module 430, a third determination module 440 and a fourth determination module 450.

[0052] Specifically, the acquisition module 410 is used to acquire the property data of the property to be evaluated and the property data of the reference property.

[0053] The first determination module 420 is used to determine the housing source index flow rate and the housing source index increase rate of the housing source to be evaluated according to the housing source data of the housing source to be evaluated.

[0054] The second determination module 430 is used to determine the housing source index flow rate and the housing source index increase rate of the reference housing source according to the housing source data of the reference housing source.

[0055] The third determination module 440 is used to determine the housing source level of the housing source to be evaluated according to the housing source indicator flow rate of the housing source to be evaluated.

[0056] The fourth determination module 450 is used to determine the label data of the current competitiveness of the house to be evaluated according to the house grade of the house to be evaluated, the increase in the house index of the house to be evaluated, and the increase in the house index of the reference house.

[0057] The housing data processing device 400 can automatically obtain the housing data of the housing to be evaluated and the reference housing, and calculate the housing index flow rate and the housing index increase based on these data, thereby realizing automation and efficiency of data processing. Compared with the manual method, this automated method greatly improves the data processing efficiency, saves time and labor costs. By determining the housing grade according to the housing index flow rate and the housing index increase, and combining the data of the reference housing to determine the current competitiveness label of the housing to be evaluated, the present invention considers more factors when annotating the label data, reduces subjective errors, and improves the accuracy and reliability of the label data. By determining the current competitiveness label of the housing to be evaluated, more accurate data support is provided for the formulation of subsequent recommendation strategies. Based on more accurate label data, the recommendation strategy of the terminal device can be optimized to improve user experience and recommendation accuracy.

[0058] In some embodiments of the present disclosure, the first determination module 420 is configured to: calculate the flow rate of the housing source indicators of the housing source to be evaluated according to the number of time periods corresponding to the housing source data of the housing source to be evaluated and the attribute indicators in the housing source data of the housing source to be evaluated each week; calculate the increase rate of the housing source indicators of the housing source to be evaluated according to the number of time periods corresponding to the housing source data of the housing source to be evaluated, the attribute indicators in the housing source data of the housing source to be evaluated each week, and the sum of the attribute indicators in the housing source data of the housing source to be evaluated.

[0059] In some embodiments of the present disclosure, the second determination module 430 is configured to: calculate the housing index flow rate of the reference housing source based on the number of time periods corresponding to the housing data of the reference housing source and the attribute indicators in the housing data of the reference housing source in each period; calculate the housing index increase of the housing source to be evaluated based on the number of time periods corresponding to the housing data of the reference housing source, the attribute indicators in the housing data of the reference housing source in each period, and the sum of the attribute indicators in the housing data of the reference housing source.

[0060] In some embodiments of the present disclosure, the third determination module 440 is configured as follows: when the flow rate of the housing source index of the housing source to be evaluated is greater than or equal to the first flow rate threshold, the housing source level of the housing source to be evaluated is determined to be a high-level housing source; when the flow rate of the housing source index of the housing source to be evaluated is greater than or equal to the second flow rate threshold and less than the first flow rate threshold, the housing source level of the housing source to be evaluated is determined to be a mid-level housing source; when the flow rate of the housing source index of the housing source to be evaluated is less than the second flow rate threshold, the housing source level of the housing source to be evaluated is determined to be a low-level housing source.

[0061] In some embodiments of the present disclosure, the fourth determination module 450 is configured to: call the label mapping table corresponding to the housing source grade according to the housing source grade of the housing source to be evaluated; determine the increase type of the housing source to be evaluated according to the increase in the housing source index of the housing source to be evaluated, and determine the increase type of the reference housing source according to the increase in the housing source index of the reference housing source; determine the label data of the current competitiveness of the housing source to be evaluated according to the increase type of the housing source to be evaluated, the increase type of the reference housing source and the label mapping table corresponding to the housing source grade.

[0062] In some embodiments of the present disclosure, determining label data of the current competitiveness of the house to be evaluated based on the price increase type of the house to be evaluated, the price increase type of the reference house, and the label mapping table corresponding to the house level includes: traversing the label mapping table based on the price increase type of the house to be evaluated and the price increase type of the reference house to obtain a mapping relationship between the price increase type of the house to be evaluated and the price increase type of the reference house; determining the label data of the current competitiveness of the house to be evaluated based on the mapping relationship.

[0063] In some embodiments of the present disclosure, the housing data processing device 400 is also used to: generate a recommended strategy for the housing to be evaluated in the current period based on the label data of the current competitiveness of the housing to be evaluated; and send the recommended strategy for the housing to be evaluated in the current period to the terminal devices in the preset list.

[0064] Figure 5 Schematic diagram of an electronic device 5 provided in an embodiment of the present disclosure. Figure 5 As shown, the electronic device 5 of this embodiment includes: a processor 501, a memory 502, and a computer program 503 stored in the memory 502 and executable on the processor 501. When the processor 501 executes the computer program 503, the steps in the above-mentioned method embodiments are implemented. Alternatively, when the processor 501 executes the computer program 503, the functions of the modules in the above-mentioned device embodiments are implemented.

[0065] The electronic device 5 may be a desktop computer, a notebook, a PDA, a cloud server, or other electronic device. The electronic device 5 may include, but is not limited to, a processor 501 and a memory 502. Those skilled in the art will appreciate that Figure 5The electronic device 5 is merely an example and does not limit the electronic device 5 , and may include more or less components than those shown in the figure, or different components.

[0066] The processor 501 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0067] The memory 502 may be an internal storage unit of the electronic device 5, for example, a hard disk or memory of the electronic device 5. The memory 502 may also be an external storage device of the electronic device 5, for example, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device 5. The memory 502 may also include both an internal storage unit of the electronic device 5 and an external storage device. The memory 502 is used to store computer programs and other programs and data required by the electronic device.

[0068] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units.

[0069] If the integrated module is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present disclosure implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. The computer program may include computer program code, and the computer program code may be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electric carrier signals and telecommunication signals.

[0070] The above embodiments are only used to illustrate the technical solutions of the present disclosure, rather than to limit them. Although the present disclosure has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present disclosure, and should all be included in the protection scope of the present disclosure.

Claims

1. A method for processing house data, characterized in that: include: Obtain the property data of the property to be evaluated and the property data of the reference property; Determine the housing source index flow rate of the housing source to be evaluated and the housing source index increase rate of the housing source to be evaluated according to the housing source data of the housing source to be evaluated; Determine the housing source index flow rate of the reference housing source and the housing source index increase rate of the reference housing source according to the housing source data of the reference housing source; Determining the housing source grade of the housing source to be evaluated according to the housing source indicator flow rate of the housing source to be evaluated; According to the housing grade of the housing to be evaluated, the housing index increase of the housing to be evaluated, and the housing index increase of the reference housing, label data of the current competitiveness of the housing to be evaluated is determined.

2. The method according to claim 1, characterized in that Determining the flow rate of the housing source index of the housing source to be evaluated and the increase rate of the housing source index of the housing source to be evaluated according to the housing source data of the housing source to be evaluated comprises: Calculate the property index flow rate of the property to be evaluated according to the number of time periods corresponding to the property data of the property to be evaluated and the attribute index in the property data of the property to be evaluated each week; The increase in the property index of the property to be evaluated is calculated according to the number of time periods corresponding to the property data of the property to be evaluated, the attribute indicators in the property data of the property to be evaluated each week, and the sum of the attribute indicators in the property data of the property to be evaluated.

3. The method according to claim 1, characterized in that Determining the housing source index flow rate and the housing source index increase rate of the reference housing source according to the housing source data of the reference housing source includes: Calculate the property index flow rate of the reference property according to the number of time periods corresponding to the property data of the reference property and the attribute index in the property data of the reference property in each period; The increase in the property index of the property to be evaluated is calculated based on the number of time periods corresponding to the property data of the reference property, the attribute indicators in the property data of the reference property in each period, and the sum of the attribute indicators in the property data of the reference property.

4. The method according to claim 1, characterized in that Determining the level of the house to be evaluated according to the house source indicator flow rate of the house to be evaluated includes: When the flow rate of the house source indicator of the house source to be evaluated is greater than or equal to the first flow rate threshold, determining that the house source level of the house source to be evaluated is a high-level house source; When the flow rate of the house source indicator of the house source to be evaluated is greater than or equal to the second flow rate threshold and less than the first flow rate threshold, determining that the house source level of the house source to be evaluated is a mid-level house source; When the house source indicator flow rate of the house source to be evaluated is less than the second flow rate threshold, it is determined that the house source grade of the house source to be evaluated is a low-level house source.

5. The method according to claim 1, characterized in that The tag data for determining the current competitiveness of the house to be evaluated according to the house grade of the house to be evaluated, the house index increase of the house to be evaluated, and the house index increase of the reference house includes: According to the property level of the property to be evaluated, calling a label mapping table corresponding to the property level; Determining the increase type of the house to be evaluated according to the increase of the house index of the house to be evaluated, and determining the increase type of the reference house according to the increase of the house index of the reference house; According to the price increase type of the to-be-evaluated property, the price increase type of the reference property, and the label mapping table corresponding to the property level, the label data of the current competitiveness of the to-be-evaluated property is determined.

6. The method according to claim 5, characterized in that According to the price increase type of the to-be-evaluated house, the price increase type of the reference house, and the label mapping table corresponding to the house level, the label data for determining the current competitiveness of the to-be-evaluated house includes: Traversing the label mapping table based on the price increase type of the to-be-evaluated property and the price increase type of the reference property to obtain a mapping relationship between the price increase type of the to-be-evaluated property and the price increase type of the reference property; According to the mapping relationship, label data of the current competitiveness of the house to be evaluated is determined.

7. The method according to any one of claims 1 to 6, characterized in that: The method further comprises: Based on the label data of the current competitiveness of the house to be evaluated, generating a recommendation strategy for the house to be evaluated in the current cycle; Send the recommended strategy for the house to be evaluated in the current cycle to the terminal devices in the preset list.

8. A housing data processing device, characterized in that: include: An acquisition module is used to acquire the property data of the property to be evaluated and the property data of the reference property; A first determination module is used to determine the housing source index flow rate of the housing source to be evaluated and the housing source index increase rate of the housing source to be evaluated according to the housing source data of the housing source to be evaluated; A second determination module is used to determine the housing source index flow rate of the reference housing source and the housing source index increase rate of the reference housing source according to the housing source data of the reference housing source; A third determination module is used to determine the housing source level of the housing source to be evaluated according to the housing source indicator flow rate of the housing source to be evaluated; The fourth determination module is used to determine the label data of the current competitiveness of the house to be evaluated according to the house grade of the house to be evaluated, the increase in the house index of the house to be evaluated, and the increase in the house index of the reference house.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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