A data collection system and method based on real estate and land taxes

Abstract

The present invention belongs to the technical field of data collection related to property and land taxes, and specifically relates to a data collection system and method based on property and land taxes. By acquiring real-time information on untaxed property and land buildings and comparing it with information on tax-paid property and land buildings, the invention can quickly and accurately identify the building types corresponding to the untaxed property and land buildings. Furthermore, the invention can intelligently determine the collection method based on the payment nodes and conditional parameters of the property tax and land use tax, thereby improving the efficiency and accuracy of data collection. By combining real-time monitoring with regular collection, the invention ensures timely updating and accurate reflection of tax information, reduces manual intervention, lowers management costs, and enables the rational allocation of system operating resources, avoiding waste of system resources.

Description

Technical Field

[0001] The present invention belongs to the technical field of data collection related to house and land taxes, and specifically relates to a data collection system and method based on house and land taxes. Background Art

[0002] With the rapid development of the real estate market, the collection and management of housing and land taxes has become increasingly complex. Traditional data collection methods often rely on manual operations, which are inefficient and prone to errors. In order to improve the accuracy and efficiency of data collection, there is an urgent need for automated and intelligent data collection systems and methods to meet the needs of modern tax management.

[0003] The data collection methods for house and land taxes in the existing technology still have some shortcomings. For example, the data collection method often simply utilizes the inherent real-time collection and periodic collection, and cannot be adjusted according to the time tax payment nodes, which will lead to the unreasonable allocation of monitoring and collection resources, which undoubtedly increases the operating cost of the system. Therefore, the present invention proposes a data collection method based on house and land taxes, aiming to solve the above problems. Summary of the Invention

[0004] The purpose of the present invention is to provide a data collection system and method based on real estate tax and land use tax, which can dynamically adjust the data collection method according to the payment nodes of real estate tax and land use tax to improve the efficiency and accuracy of data collection while reducing the system operation cost.

[0005] The technical solutions adopted by the present invention are as follows:

[0006] A data collection method based on housing and land taxes, comprising:

[0007] Obtain tax-paid building and land information, wherein the building and land information includes building type, building area, and number of buildings;

[0008] Collecting the payment information of property tax and land use tax under each of the house and building information and compiling it into a reference data set;

[0009] Collecting payment nodes of property tax and land use tax from the reference dataset, and determining a collection method of property tax and land use tax based on the payment nodes, wherein the collection method includes periodic collection and real-time collection;

[0010] Obtain real-time information on untaxed buildings and soil, and compare it with tax-paid buildings and soil information to determine the building type corresponding to the untaxed buildings and soil;

[0011] Data collection is performed based on the reference data set corresponding to the building type matching and the collection method of the property tax and land use tax corresponding to the unpaid house and land building information, and the collection results are uploaded to a preset database for storage.

[0012] In a preferred solution, after the tax-paid house and land construction information is collected, data preprocessing is performed simultaneously, and the steps are as follows:

[0013] Obtain tax-paid house, land, and building information, and perform deduplication processing to eliminate duplicate items in the tax-paid house, land, and building information;

[0014] Add timestamps to the deduplicated building and soil information to form benchmark feature data with time series characteristics;

[0015] The benchmark feature data is classified and processed to obtain multiple building information subsets.

[0016] In a preferred embodiment, the step of collecting the payment information of the property tax and the land use tax under each of the house and land construction information and aggregating the information into a reference data set includes:

[0017] Extracting the payment time nodes of the property tax and the land use tax from the payment information and recording them as the first condition parameter;

[0018] performing an offset process on the first condition parameter, and determining a sample period according to the offset result;

[0019] Collect the amount of property tax and land use tax paid during the sample period and record it as the second condition parameter;

[0020] Performing correlation evaluation processing on adjacent sample time periods according to the second condition parameter to obtain correlated time periods and independent time periods;

[0021] The associated time periods are merged until the merged associated time periods meet the standards of independent time periods, and then the payment information of the property tax and land use tax in each of the independent time periods is summarized as a reference data set.

[0022] In a preferred embodiment, there are multiple payment time nodes, and the time intervals between adjacent payment time nodes are consistent;

[0023] The offset mode of the first condition parameter is bidirectional equidistant offset, and the unidirectional offset length of the first condition parameter is greater than half of the time length between adjacent payment time nodes.

[0024] In a preferred embodiment, the step of performing correlation evaluation processing on adjacent sample time periods based on the second condition parameter to obtain correlated time periods and independent time periods includes:

[0025] Obtaining a second condition parameter under each of the sample time periods;

[0026] Obtaining a correlation evaluation threshold, and directly recording the sample periods under the second condition parameter that is greater than the correlation evaluation threshold as independent periods;

[0027] performing summation processing on the second condition parameters in adjacent sample time periods to obtain an associated condition parameter, and comparing the associated condition parameter with an associated evaluation threshold;

[0028] When the correlation condition parameter is greater than or equal to the correlation evaluation threshold, directly merging the adjacent sample time periods into independent time periods;

[0029] When the association condition parameter is less than the association evaluation threshold, the adjacent sample periods are recorded as association periods and merged simultaneously, and the association evaluation process is continued on the merged sample periods until all are output as independent periods.

[0030] In a preferred embodiment, the step of determining the collection method of the property tax and the land use tax according to the payment node includes:

[0031] Counting the length of each independent time period and recording it as a precondition parameter;

[0032] Obtaining a classification threshold, and comparing the classification threshold with a precondition parameter;

[0033] If the precondition parameter is less than the classification threshold, it indicates that the collection process of the property tax and the land use tax in the independent time period is frequent, and the collection method of the property tax and the land use tax is determined to be real-time collection;

[0034] If the precondition parameter is greater than or equal to the classification threshold, it indicates that the collection process of the property tax and land use tax in the independent time period is dispersed, and the collection method of the property tax and land use tax is determined to be periodic collection.

[0035] In a preferred embodiment, the step of obtaining the tax-unpaid house and soil construction information in real time and comparing it with the tax-paid house and soil construction information to determine the building type corresponding to the tax-unpaid house and soil construction includes:

[0036] Obtain information on untaxed buildings and land, as well as tax-paid buildings and land;

[0037] Vectorizing the untaxed house, land, and building information and the taxed house, land, and building information to obtain a feature vector to be compared and a reference feature vector;

[0038] Obtaining a pairing function, inputting the feature vector to be compared and the reference feature vector into the pairing function, and recording the output of the pairing function as a pairing score;

[0039] The pairing scores are arranged in descending order, and the untaxed house and land building information and the taxed house and land building information with the highest pairing score are paired, and the building type of the taxed house and land building information is output simultaneously, and then the building type corresponding to the untaxed house and land building is output.

[0040] In a preferred embodiment, the step of collecting data based on the method of collecting property tax and land use tax for the unpaid house and land construction information includes:

[0041] Obtain the building types corresponding to untaxed buildings and the collection methods of property taxes and land use taxes in the reference dataset for the building types;

[0042] Under the said regular collection, data collection of property tax and land use tax under unpaid house and land construction information is performed at fixed intervals;

[0043] Under the real-time collection, real-time monitoring is performed on the property tax and land use tax under the unpaid house and land construction information, and data collection is immediately performed when the payment of property tax or land use tax is detected.

[0044] The present invention further provides a data collection system based on the housing and land taxes, using the above-mentioned data collection method based on the housing and land taxes, comprising:

[0045] A data acquisition module, the data acquisition module is used to obtain tax-paid house and land construction information, wherein the house and land construction information includes building type, building area and number of buildings;

[0046] A reference module, the reference module is used to collect the payment information of property tax and land use tax under each of the house and land construction information, and compile it into a reference data set;

[0047] a method evaluation module, the method evaluation module being configured to collect payment nodes of property tax and land use tax from the reference data set and determine a collection method of property tax and land use tax based on the payment nodes, wherein the collection method includes a periodic collection method and a real-time collection method;

[0048] A classification module is used to obtain information on untaxed houses and land in real time, compare it with information on taxed houses and land, and determine the building type corresponding to the untaxed houses and land;

[0049] A method determination module is used to perform data collection based on the reference data set corresponding to the building type and the collection method of the property tax and land use tax corresponding to the unpaid house and land construction information, and upload the collection results to a preset database for storage.

[0050] And, an electronic device, comprising:

[0051] at least one processor;

[0052] and a memory communicatively coupled to the at least one processor;

[0053] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the above-mentioned data collection method based on the housing and land tax.

[0054] The technical effects achieved by the present invention are:

[0055] The data collection method based on the house and land tax in the present invention can quickly and accurately identify the building type corresponding to the untaxed house and land building by acquiring the untaxed house and land building information in real time and comparing it with the taxed house and land building information. At the same time, it can also intelligently determine the collection method according to the payment nodes and condition parameters of the property tax and land use tax, thereby improving the efficiency and accuracy of data collection. By combining real-time monitoring and regular collection, it ensures the timely updating and accurate reflection of tax information, reduces manual intervention, reduces management costs, enables the system operation resources to be reasonably allocated, and avoids the waste of system resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 It is a schematic flow chart of the method of the present invention;

[0057] Figure 2 It is a schematic diagram of the system modules of the present invention;

[0058] Figure 3 It is a schematic structural diagram of an electronic device of the present invention. DETAILED DESCRIPTION

[0059] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0060] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0061] Secondly, the term "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in a preferred embodiment" appearing in various places throughout this specification does not necessarily refer to the same embodiment, nor does it constitute a separate or selective embodiment that is mutually exclusive of other embodiments.

[0062] See also Figure 1 As shown, the present invention provides a data collection method based on housing and land taxes, comprising:

[0063] S1. Obtain tax-paid building and land information, where the building and land information includes building type, building area, and number of buildings;

[0064] In step S1, when optimizing data collection for real estate and land tax information, it is first necessary to obtain relevant information on real estate and land buildings that have fulfilled their tax obligations, namely, real estate, land and building information. Real estate, land and building information includes but is not limited to building type, building area and number of buildings. This information can be obtained through the existing tax system or through cooperation with relevant departments. After the collection of tax-paid real estate, land and building information is completed, data preprocessing is performed simultaneously. The steps are as follows:

[0065] Obtain tax-paid house, land, and building information, and perform deduplication processing to eliminate duplicate items in the tax-paid house, land, and building information;

[0066] Add timestamps to the deduplicated building and soil information to form benchmark feature data with time series characteristics;

[0067] Classify and process the benchmark feature data to obtain multiple building information subsets;

[0068] Specifically, after completing the collection of tax-paid house, soil and building information, corresponding data preprocessing is required to ensure the accuracy and availability of the data. First, it is necessary to obtain the tax-paid house, soil and building information and perform deduplication processing on it to eliminate duplicate items. The purpose is to ensure the accuracy of subsequent analysis and avoid errors caused by duplicate data. After the deduplication processing is completed, a timestamp will be added to the house, soil and building information to form benchmark feature data with time series characteristics. The addition of the timestamp is to record the time attributes of each building information in order to better understand the changes in the house, soil and building information. Finally, the benchmark feature data will be classified to obtain multiple building information subsets. The purpose of the classification processing is to classify building information with similar characteristics into the same subset, so as to facilitate subsequent analysis and processing.

[0069] S2. Collect the property tax and land use tax payment information for each building and construction information and compile it into a reference dataset;

[0070] In step S2, after the building information is determined, it is necessary to collect the property tax and land use tax payment information corresponding to each building. The payment information will be aggregated and organized into multiple reference data sets according to the building type to facilitate subsequent analysis and processing. The steps of collecting the property tax and land use tax payment information for each building information and aggregating them into reference data sets include:

[0071] Extract the payment time of property tax and land use tax from the payment information and record it as the first condition parameter;

[0072] Performing an offset process on the first condition parameter, and determining a sample period according to the offset result;

[0073] Collect the amount of property tax and land use tax paid during the sample period and record it as the second condition parameter;

[0074] Performing correlation evaluation processing on adjacent sample periods according to the second condition parameter to obtain correlated periods and independent periods;

[0075] The associated time periods are merged until they meet the criteria for independent time periods. The payment information of property tax and land use tax in each independent time period is then aggregated into a reference data set.

[0076] In order to ensure that the payment information of property tax and land use tax for each house and land building can be accurately collected and compiled into a reference data set, it is necessary to first carefully extract the specific payment time nodes of property tax and land use tax from the existing payment information. There are multiple payment time nodes, and the time intervals between adjacent payment time nodes are consistent. The payment time nodes will be used as the first condition parameter for subsequent analysis, and then the first condition parameter will be offset. The purpose of the offset processing is to determine a suitable sample period so that the payment of property tax and land use tax can be more accurately analyzed and evaluated. Here, it needs to be explained Yes, the offset method of the first condition parameter is bidirectional equidistant offset, and the unidirectional offset length of the first condition parameter is greater than half of the time length between adjacent payment time nodes, so as to cover the volatility of payment information. After determining the sample period, it is necessary to collect the amount of property tax and land use tax payments within the period. The payment amount will be used as the second condition parameter for subsequent analysis. After that, the adjacent sample periods will be associated with each other. Through the association evaluation, the associated periods can be merged to form independent periods, and the property tax and land use tax payment information in the independent periods can be summarized to form a complete reference data set.

[0077] Here, the step of performing correlation evaluation processing on adjacent sample time periods based on the second condition parameter to obtain correlated time periods and independent time periods includes:

[0078] Obtaining the second condition parameter for each sample period;

[0079] Obtaining a correlation evaluation threshold, and directly recording the sample periods under the second condition parameter that is greater than the correlation evaluation threshold as independent periods;

[0080] Summing the second condition parameters in adjacent sample time periods to obtain an associated condition parameter, and comparing the associated condition parameter with an associated evaluation threshold;

[0081] When the correlation condition parameter is greater than or equal to the correlation evaluation threshold, the adjacent sample periods are directly merged into independent periods;

[0082] When the correlation condition parameter is less than the correlation evaluation threshold, the adjacent sample periods are recorded as correlation periods and merged simultaneously, and the correlation evaluation process is continued for the merged sample periods until all are output as independent periods.

[0083] In the above, when evaluating the sample periods, it is first necessary to obtain the second condition parameter of each sample period and pre-set a correlation evaluation threshold. The correlation evaluation threshold will be used to determine whether the sample periods have sufficient correlation. Once the second condition parameter value of a sample period is greater than the correlation evaluation threshold, it can be directly recorded as an independent period. Then, the second condition parameters of adjacent sample periods are summed to obtain a correlation condition parameter. The correlation condition parameter reflects the degree of correlation between adjacent periods. At the same time, the correlation condition parameter is compared with the correlation evaluation threshold. If the correlation condition parameter is greater than or equal to the correlation evaluation threshold, it means that the correlation between adjacent sample periods is strong. Therefore, the corresponding adjacent sample periods can be directly merged into an independent period. On the contrary, if the correlation condition parameter is less than the correlation evaluation threshold, it indicates that the correlation between adjacent sample periods is weak. Therefore, the corresponding adjacent sample periods are recorded as correlated periods and need to be merged to further analyze the correlation between them. After the merging process, the correlation evaluation process is continued for the merged sample periods until all sample periods are evaluated and output as independent periods. This process will continue until the evaluation process of all sample periods is completed.

[0084] S3. Collecting payment nodes of property tax and land use tax from the reference dataset, and determining a collection method for property tax and land use tax based on the payment nodes, wherein the collection method includes periodic collection and real-time collection;

[0085] In step S3, based on the reference dataset, payment nodes for property tax and land use tax are further collected. The payment nodes are used to determine the collection method for property tax and land use tax. In this embodiment, the collection method can be divided into two types: periodic collection and real-time collection. Periodic collection refers to data collection at fixed time intervals, while real-time collection refers to data collection immediately when the tax is paid. The steps of determining the collection method for property tax and land use tax based on the payment nodes include:

[0086] Count the length of each independent period and record it as the precondition parameter;

[0087] Get the classification threshold and compare the classification threshold with the precondition parameter;

[0088] If the precondition parameter is less than the classification threshold, it indicates that the collection process of property tax and land use tax in the independent period is frequent, and the collection method of property tax and land use tax is determined to be real-time collection;

[0089] If the precondition parameter is greater than or equal to the classification threshold, it indicates that the collection process of property tax and land use tax in the independent period is decentralized, and the collection method of property tax and land use tax is determined to be periodic collection;

[0090] Specifically, in order to ensure that the collection method of property tax and land use tax can be reasonably arranged according to the specific payment nodes, it is necessary to first count the length of each independent time period and record it as a precondition parameter. Then, it is necessary to obtain the corresponding classification threshold. The classification threshold is a pre-set standard used to judge the collection frequency of property tax and land use tax in an independent time period. These classification thresholds are compared with the precondition parameters previously counted. If the comparison shows that the precondition parameters are less than the classification threshold, it means that the collection process of property tax and land use tax is relatively frequent in the independent time period. In this case, The collection method of property tax and land use tax will be determined as real-time collection. Real-time collection means that the tax department needs to collect and process data immediately when each payment node arrives to ensure timely collection and accurate recording of taxes. On the contrary, if the precondition parameter is greater than or equal to the classification threshold, it means that the collection process of property tax and land use tax is relatively scattered within an independent time period. In this case, the collection method of property tax and land use tax will be determined as periodic collection. Periodic collection means that the tax department can concentrate on data collection and processing within each fixed time period, thereby improving work efficiency and reducing resource consumption caused by frequent operations.

[0091] S4. Obtaining in real time the information of untaxed houses, land, and buildings, and comparing it with the information of tax-paid houses, land, and buildings, to determine the building type corresponding to the untaxed houses, land, and buildings;

[0092] In step S4, in order to ensure the completeness and accuracy of the data, it is also necessary to obtain in real time the information of houses, land and buildings for which property tax and land use tax have not yet been paid. By comparing the information of houses, land and buildings for which tax has been paid with the information of houses, land and buildings for which tax has been paid, the specific building type of the houses, land and buildings for which tax has not been paid can be determined. The steps of obtaining the information of houses, land and buildings for which tax has not been paid in real time and comparing it with the information of houses, land and buildings for which tax has been paid to determine the building type corresponding to the houses, land and buildings for which tax has not been paid include:

[0093] Obtain information on untaxed buildings and land, as well as tax-paid buildings and land;

[0094] Vectorize the untaxed house, land, and building information and the taxed house, land, and building information to obtain the feature vector to be compared and the reference feature vector;

[0095] Obtain a pairing function, input the feature vector to be compared and the reference feature vector into the pairing function, and record the output of the pairing function as a pairing score;

[0096] Arrange the matching scores from high to low, and match the untaxed house, land, and building information with the highest matching score with the tax-paid house, land, and building information, and simultaneously output the building type of the tax-paid house, land, and building information, and then output the building type corresponding to the untaxed house, land, and building information;

[0097] Specifically, in order to obtain the building information of unpaid property tax and land tax in real time and compare and analyze it with the building information of tax-paid buildings to determine the building type corresponding to the unpaid buildings, it is first necessary to obtain the house and land building information of unpaid property tax and land tax in real time. At the same time, it is also necessary to obtain the house and land building information of those that have paid the tax. In order to facilitate comparison and analysis, it is necessary to vectorize the house and land building information of unpaid tax and the house and land building information of tax-paid buildings. In this way, the house and land building information of unpaid tax and the house and land building information of tax-paid buildings can be converted into feature vectors in numerical form, which are respectively called the feature vector to be compared and the reference feature vector. In order to further analyze the similarity or difference between these feature vectors, it is necessary to obtain a preset pairing function (the expression of the pairing function is: In the formula, R represents the pairing score, n represents the number of feature points in the feature vector to be evaluated and the reference feature vector, and a i and b i Represent the feature vector to be evaluated and the reference feature vector respectively), the pairing function can accept the feature vector to be compared and the reference feature vector as input, and output a pairing score to reflect the degree of matching between the untaxed house, land and building information and the taxed house, land and building information. After obtaining the pairing score, it is necessary to arrange it in descending order. In this way, the most likely matching building information pair can be found. Specifically, the untaxed house, land and building information and the taxed house, land and building information corresponding to the highest pairing score will be selected for pairing. Finally, in order to determine the building type corresponding to the untaxed house, land and building, it is necessary to synchronously output the building type of the taxed house, land and building information paired with it. In this way, the type of the taxed building can be directly output as the corresponding type of the untaxed building.

[0098] S5. Perform data collection based on the reference dataset corresponding to the building type and the collection method of the property tax and land use tax corresponding to the unpaid house and land building information, and upload the collection results to a preset database for storage;

[0099] In step S5, the corresponding reference dataset is matched according to the building type, and the collection method of the property tax and land use tax corresponding to the unpaid house, land and building information is combined. Based on these matching results, the corresponding data collection work will be performed. After the collection is completed, the collection results will be uploaded to a pre-set database for storage to facilitate subsequent query and analysis. The steps of performing data collection based on the collection method of the property tax and land use tax for the unpaid house, land and building information include:

[0100] Obtain the building type corresponding to the untaxed buildings and the collection method of property tax and land use tax in the corresponding reference dataset under the building type;

[0101] Under regular collection, data collection of property tax and land use tax under unpaid house and land construction information is carried out at fixed intervals;

[0102] Real-time data collection enables real-time monitoring of property tax and land use tax on unpaid building and construction information, and immediate data collection upon detection of property tax or land use tax payment behavior.

[0103] Specifically, based on the information on houses and land buildings that have not paid property tax and land use tax, a matched data collection method is needed to perform the collection of property tax and land use tax. First, it is necessary to obtain relevant information on houses and land buildings that have not paid property tax and land use tax, including building type. At the same time, the existing property tax and land use tax collection methods in the dataset will be referenced and the specific collection method will be determined based on different building types. Secondly, in the case of periodic collection, a fixed time interval will be set, such as weekly, monthly, or quarterly, to collect data on houses and land buildings that have not paid property tax and land use tax. The periodic collection method helps to update and maintain relevant data in a timely manner, ensuring the accuracy and timeliness of the information. In the case of real-time collection, the information on houses and land buildings that have not paid property tax and land use tax will be monitored in real time. Once a property tax or land use tax payment is detected, data collection will be carried out immediately to ensure that the latest payment information can be quickly captured. This collection method is suitable for situations where payments are frequent, such as during the delivery period of new houses. This method can avoid data redundancy and reasonably optimize the collection efficiency of property and land taxes.

[0104] See also Figure 2 A data collection system based on housing and land taxes, using the above-mentioned data collection method based on housing and land taxes, comprises:

[0105] The data collection module is used to obtain tax-paid house and land construction information, wherein the house and land construction information includes building type, building area and number of buildings;

[0106] Reference module: The reference module is used to collect the payment information of property tax and land use tax under each building information and summarize it into a reference data set;

[0107] Method evaluation module, which is used to collect the payment nodes of property tax and land use tax from the reference data set and determine the collection method of property tax and land use tax based on the payment nodes. The collection methods include periodic collection method and real-time collection method;

[0108] The classification module is used to obtain the information of untaxed houses and land in real time, compare it with the information of taxed houses and land, and determine the building type corresponding to the untaxed houses and land;

[0109] The method determination module is used to perform data collection based on the reference data set corresponding to the building type, as well as the collection method of the property tax and land use tax corresponding to the unpaid house and land building information, and upload the collection results to the preset database for storage.

[0110] In the above, the system includes a data collection module, a reference module, a method evaluation module, a classification module and a method determination module. These modules work together to ensure the efficiency and accuracy of the entire data collection process. The data collection module is responsible for collecting relevant information on real estate and land buildings that have completed tax obligations, covering multiple dimensions such as building type, building area and number of buildings, ensuring the comprehensiveness and accuracy of the data. The role of the reference module is to collect the payment status of real estate tax and land use tax under each real estate and land building information, and summarize it into a detailed reference data set, which provides an important basis for subsequent analysis and decision-making. The method evaluation module extracts the payment node information of real estate tax and land use tax from the reference data set, and determines the payment node information of real estate tax and land use tax based on the payment node information. The collection method of property tax and land use tax can be divided into two types: regular collection and real-time collection, so that the most appropriate collection strategy can be flexibly selected according to the actual situation. The classification module obtains the real estate and land building information of the property tax and land use tax that have not yet paid in real time, and compares and analyzes it with the building information that has paid the tax. In this way, the type of unpaid tax buildings can be accurately identified, thereby providing support for subsequent processing. The method determination module matches the corresponding reference data set according to the building type, and determines the collection method of property tax and land use tax in combination with the unpaid tax building information. Once the collection method is determined, the system will perform data collection according to the established process, and upload the collected results to the pre-set database for storage and management, providing strong data support for the tax authorities.

[0111] See also Figure 3 , an electronic device, the electronic device comprising:

[0112] at least one processor;

[0113] and a memory communicatively coupled to the at least one processor;

[0114] The memory stores a computer program that can be executed by at least one processor, and the computer program is executed by at least one processor so that the at least one processor can execute the above-mentioned data collection method based on the housing and land tax.

[0115] The processor of the electronic device may be

[0116] A central processing unit (CPU) or microprocessor is responsible for executing instructions in computer programs and handling tasks such as data acquisition, analysis, and storage. Memory, which can be random access memory (RAM), read-only memory (ROM), or other forms of non-volatile memory, is used to store computer programs and temporary or permanent data. Electronic devices may also include an arithmetic unit, input devices, and output devices. The arithmetic unit is used to perform data processing and computing tasks, input devices such as a keyboard and mouse allow users to interact with the electronic device, and output devices such as displays and printers are used to display processing results and output data.

[0117] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, apparatus, article, or method comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, apparatus, article, or method. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, apparatus, article, or method comprising the element.

[0118] The foregoing is merely a preferred embodiment of the present invention. It should be noted that those skilled in the art may make various improvements and modifications without departing from the principles of the present invention, and such improvements and modifications are also within the scope of protection of the present invention. Structures, devices, and operating methods not specifically described or explained herein shall, unless otherwise specified or limited, be implemented in accordance with conventional means in the art.

Claims

1. A data collection method based on housing and land taxes, characterized by: include: Obtain tax-paid building and land information, wherein the building and land information includes building type, building area, and number of buildings; Collecting the payment information of property tax and land use tax under each of the house and building information and compiling it into a reference data set; Collecting payment nodes of property tax and land use tax from the reference dataset, and determining a collection method of property tax and land use tax based on the payment nodes, wherein the collection method includes periodic collection and real-time collection; Obtain real-time information on untaxed buildings and soil, and compare it with tax-paid buildings and soil information to determine the building type corresponding to the untaxed buildings and soil; Based on the information on houses and land buildings that have not paid property tax and land use tax, a matched data collection method is adopted to perform the collection of property tax and land use tax, and obtain relevant information on houses and land buildings that have not paid property tax and land use tax. At the same time, refer to the existing property tax and land use tax collection methods in the reference data set, and determine the specific collection method according to different building types. Secondly, in the case of periodic collection, set a fixed time interval to collect data on the information on houses and land buildings that have not paid property tax and land use tax. In the case of real-time collection, the information on houses and land buildings that have not paid property tax and land use tax is monitored in real time. When it is detected that there is a payment behavior of property tax or land use tax, data collection is immediately carried out, and the collection results are uploaded to the preset database for storage.

2. The data collection method based on the housing and land tax according to claim 1 is characterized by: After the tax-paid house and land construction information is collected, data preprocessing is performed simultaneously, and the steps are as follows: Obtain tax-paid house, land, and building information, and perform deduplication processing to eliminate duplicate items in the tax-paid house, land, and building information; Add timestamps to the deduplicated building and soil information to form benchmark feature data with time series characteristics; The benchmark feature data is classified and processed to obtain multiple building information subsets.

3. The data collection method based on the housing and land tax according to claim 2 is characterized by: The step of collecting the payment information of the property tax and the land use tax under each of the house and land construction information and aggregating them into a reference data set includes: Extracting the payment time nodes of the property tax and the land use tax from the payment information and recording them as the first condition parameter; performing an offset process on the first condition parameter, and determining a sample period according to the offset result; Collect the amount of property tax and land use tax paid during the sample period and record it as the second condition parameter; Performing correlation evaluation processing on adjacent sample time periods according to the second condition parameter to obtain correlated time periods and independent time periods; The associated time periods are merged until the merged associated time periods meet the standards of independent time periods, and then the payment information of the property tax and land use tax in each of the independent time periods is summarized as a reference data set.

4. The data collection method based on the housing and land tax according to claim 3 is characterized by: There are multiple payment time nodes, and the time intervals between adjacent payment time nodes are consistent; The offset mode of the first condition parameter is bidirectional equidistant offset, and the unidirectional offset length of the first condition parameter is greater than half of the time length between adjacent payment time nodes.

5. The data collection method based on the housing and land tax according to claim 3 is characterized by: The step of performing association evaluation processing on adjacent sample time periods based on the second condition parameter to obtain associated time periods and independent time periods includes: Obtaining a second condition parameter under each of the sample time periods; Obtaining a correlation evaluation threshold, and directly recording the sample periods under the second condition parameter that is greater than the correlation evaluation threshold as independent periods; performing summation processing on the second condition parameters in adjacent sample time periods to obtain an associated condition parameter, and comparing the associated condition parameter with an associated evaluation threshold; When the correlation condition parameter is greater than or equal to the correlation evaluation threshold, directly merging the adjacent sample time periods into independent time periods; When the association condition parameter is less than the association evaluation threshold, the adjacent sample periods are recorded as association periods and merged simultaneously, and the association evaluation process is continued on the merged sample periods until all are output as independent periods.

6. The data collection method based on the housing and land tax according to claim 5 is characterized by: The step of determining the collection method of the property tax and the land use tax according to the payment node includes: Counting the length of each independent time period and recording it as a precondition parameter; Obtaining a classification threshold, and comparing the classification threshold with a precondition parameter; If the precondition parameter is less than the classification threshold, it indicates that the collection process of the property tax and the land use tax in the independent time period is frequent, and the collection method of the property tax and the land use tax is determined to be real-time collection; If the precondition parameter is greater than or equal to the classification threshold, it indicates that the collection process of the property tax and land use tax in the independent time period is dispersed, and the collection method of the property tax and land use tax is determined to be periodic collection.

7. The data collection method based on the housing and land tax according to claim 1 is characterized by: The step of obtaining the tax-unpaid house and soil construction information in real time and comparing it with the tax-paid house and soil construction information to determine the building type corresponding to the tax-unpaid house and soil construction includes: Obtain information on untaxed buildings and land, as well as tax-paid buildings and land; Vectorizing the untaxed house, land, and building information and the taxed house, land, and building information to obtain a feature vector to be compared and a reference feature vector; Obtaining a pairing function, inputting the feature vector to be compared and the reference feature vector into the pairing function, and recording the output of the pairing function as a pairing score; The pairing scores are arranged in descending order, and the untaxed house and land building information and the taxed house and land building information with the highest pairing score are paired, and the building type of the taxed house and land building information is output simultaneously, and then the building type corresponding to the untaxed house and land building is output.

8. The data collection method based on housing and land taxes according to claim 1 is characterized by: The steps of collecting property tax and land use tax using a matched data collection method based on the information of houses and land buildings for which property tax and land use tax have not been paid include: Obtain the building types corresponding to untaxed buildings and the collection methods of property taxes and land use taxes in the reference dataset for the building types; Under the said regular collection, data collection of property tax and land use tax under unpaid house and land construction information is performed at fixed intervals; Under the real-time collection, real-time monitoring is performed on the property tax and land use tax under the unpaid house and land construction information, and data collection is immediately performed when the payment of property tax or land use tax is detected.

9. A data collection system based on real estate and land taxes, characterized by: The data collection method based on the housing and land tax according to any one of claims 1 to 8 comprises: A data acquisition module, the data acquisition module is used to obtain tax-paid house and land construction information, wherein the house and land construction information includes building type, building area and number of buildings; A reference module, the reference module is used to collect the payment information of property tax and land use tax under each of the house and land construction information, and compile it into a reference data set; a method evaluation module, the method evaluation module being configured to collect payment nodes of property tax and land use tax from the reference data set and determine a collection method of property tax and land use tax based on the payment nodes, wherein the collection method includes a periodic collection method and a real-time collection method; A classification module is used to obtain information on untaxed houses and land in real time, compare it with information on taxed houses and land, and determine the building type corresponding to the untaxed houses and land; A method determination module is used to collect property tax and land use tax based on the information of houses and land buildings for which property tax and land use tax have not been paid, adopt a matched data collection method to obtain relevant information of houses and land buildings for which property tax and land use tax have not been paid, and at the same time refer to the existing property tax and land use tax collection methods in the reference data set to determine the specific collection method according to different building types. Secondly, in the case of periodic collection, a fixed time interval is set to collect data on the information of houses and land buildings for which property tax and land use tax have not been paid. In the case of real-time collection, the information of houses and land buildings for which property tax and land use tax have not been paid is monitored in real time. When a payment behavior of property tax or land use tax is detected, data collection is immediately performed, and the collection results are uploaded to a preset database for storage.

10. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively coupled to the at least one processor; Wherein, the memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the data collection method based on the house and land tax as described in any one of claims 1 to 8.

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