CN-121996647-A - Real estate data non-correspondence auditing method, system and terminal based on big data

CN121996647ACN 121996647 ACN121996647 ACN 121996647ACN-121996647-A

Abstract

The invention belongs to the technical field of data management, and particularly relates to a real estate data non-correspondence auditing method, system and terminal based on big data. According to the invention, the real estate data information is matched with the initial comparison items in the data set one by relying on the comparison data set constructed by the data to be detected and the preset database, and then all the initial comparison items with high matching degree are screened and collected according to the comparison result of the matching value and the matching threshold value, so that the standard data is formed. The construction of standard data avoids systematic deviation possibly introduced by taking a single fixed data source as a comparison standard, improves the accuracy of subsequent non-corresponding item determination, and is a tamping foundation for the implementation of the whole auditing process.

Inventors

ZHANG XIANG
LI FANGJIE
WU JINYANG

Assignees

连云港市不动产交易登记中心

Dates

Publication Date: 20260508
Application Date: 20260128

Claims (10)

1. The real estate data non-corresponding auditing method based on big data is characterized by comprising the following steps: The method comprises the steps of comparing real estate data information with standard data to determine non-corresponding items, identifying and classifying error items in a data set associated with the non-corresponding items to output processing matters, confirming the non-corresponding items according to the processing matters to generate confirmed items, and verifying the confirmed items based on historical data to output a final confirmed result; wherein, the standard data is determined by the following way: Constructing a comparison data set based on real estate data information and record contents in a preset database; Setting real estate data information as data to be inspected, and setting data items in a comparison data set as initial comparison items; respectively matching the data to be detected with each item in the initial comparison items to output a matching value; and comparing the matching value with a preset matching threshold, if the matching value is larger than the matching threshold, reserving corresponding initial comparison items, and aggregating all reserved initial comparison items to form standard data.
2. The real estate data non-correspondence auditing method based on big data according to claim 1, characterized in that, The real estate data information to be verified and the data set associated with the real estate data information are acquired before the real estate data information is compared with the standard data.
3. The big data based real estate data non-correspondence auditing method of claim 2 wherein the real estate data information includes at least one of a equity certificate number, equity name, equity identity number, house seating, house type, house area, and real estate unit number.
4. The large data-based real estate data non-correspondence auditing method according to claim 1, characterized in that the identifying and classifying the error items in the data set associated with the non-correspondence items includes: Acquiring real estate registration data and property registration data from the associated data set, defining the value of the real estate registration data as a first value and the value of the property registration data as a second value; calculating the ratio of the first value to the second value, and judging whether the ratio is in a preset ratio range; if the ratio is within the preset ratio range, identifying the real estate registration data as first calibration data, and marking the rest data items in the associated data set as suspected error items; If the ratio exceeds the preset ratio range, the real estate registration data is set as a reference standard, the rest data items in the associated data set are compared with the reference standard to determine an offset value, the data item with the smallest offset value is determined as second calibration data, and the rest data items except the first calibration data and the second calibration data are marked as suspected error items.
5. The real estate data non-correspondence auditing method based on big data according to claim 4, characterized in that, After the second calibration data is determined, performing numerical comparison on the first calibration data and the second calibration data, and determining replacement data according to a comparison result so as to replace suspected error items by the replacement data; Wherein the determination of the replacement data comprises: If the value of the first calibration data is the same as the value of the second calibration data, determining the value as the replacement data; and if the values are different, selecting one of the first calibration data and the second calibration data as a reference item, selecting the other one as a target item, adjusting the value of the target item based on the modified offset value associated with the time node until the adjusted value is the same as the value of the reference item, and determining the adjusted value as the replacement data.
6. The large-data-based real estate data non-correspondence auditing method according to claim 1, characterized in that the validation processing of the non-correspondence item according to the processing item to generate the validation item includes: The method includes the steps of generating a number of proofreading items equal to the number of non-corresponding items, performing a validation operation on all the proofreading items, and uniformly generating the validated proofreading items after the validation operation of all the proofreading items is completed.
7. The large data-based real estate data non-correspondence auditing method of claim 1, wherein verifying the validation item based on the historical data to output a final validation result includes: acquiring a time interval covering the generation time of the confirmation item, and extracting historical effective data from the time interval; Comparing the historical valid data with the validation term to evaluate consistency; And determining the effective use period of the confirmation item according to the consistency evaluation result, and outputting the effective use period as a final confirmation result.
8. Real estate data non-corresponding auditing system based on big data is characterized by comprising the following modules: The data auditing module is used for comparing the real estate data information with standard data to determine non-corresponding items; the non-corresponding item processing module is used for carrying out identification and classification processing on the error items in the data set associated with the non-corresponding items so as to output processing items; The confirmation item generation module is used for carrying out confirmation processing on the non-corresponding item according to the processing items so as to generate a confirmation item; and the result verification module is used for verifying the confirmation item based on the historical data so as to output a final confirmation result.
9. The big data based real estate data non-correspondence auditing system of claim 8 wherein the non-correspondence item processing module is for: Acquiring real property registration data and property registration data from the associated data set; calculating the ratio of the value of the real estate registration data to the value of the property registration data; And respectively marking the data items in the associated data set as first check data, second check data or suspected error items according to whether the ratio is in a preset ratio range.
10. The real estate data based on big data does not correspond to the auditing terminal, and is characterized by comprising a processor and a memory; A computer program is stored in a memory, the computer program being configured to implement the big data based real estate data non-correspondence auditing method according to any of claims 1 to 7 when executed by a processor.

Description

Real estate data non-correspondence auditing method, system and terminal based on big data Technical Field The invention belongs to the technical field of data management, and particularly relates to a real estate data non-correspondence auditing method, system and terminal based on big data. Background With the continuous deepening of digital transformation in the field of real estate, a real estate data management system has become an infrastructure for guaranteeing property safety and optimizing real estate resource allocation. But real estate data cover multi-source heterogeneous information such as house-ground integrated registration, cadastral mapping, planning approval, right limitation state and the like, and the real estate data are complex in structure, high in updating frequency and strong in dynamic property. When the accuracy, the integrity and the consistency of the system data cannot be effectively ensured, the real estate registration book information is directly distorted, and finally the processing efficiency and the public trust of the related businesses such as mortgage loan, property right transaction, tax verification and the like are influenced. In the prior art, auditing is limited to shallow rules such as data format verification and field integrity verification, lacks accurate judging capability for cross-business and cross-period data deep logic contradiction, and is faced with historical data subjected to multiple transfer, change and correction, and the current system generally lacks interpretable evolution traceability, and mostly adopts simple snapshot coverage or binary comparison method, so that whether data change is transacted depending on legal correction program or administrative permission cannot be intelligently screened. The defect is easy to judge legal correction errors as data errors and reject, and simultaneously, new data without legal rights sources is easy to be illegally accepted, historical effective registration records are covered, the whole data quality of real estate can be continuously lowered, and potential laws and business hidden dangers can be buried for a real estate right circulation chain. In view of the above, the invention provides a real estate data non-correspondence auditing method, system and terminal based on big data. Disclosure of Invention The invention aims to provide a real estate data non-correspondence auditing method, a system and a terminal based on big data, so as to solve the problems of incomplete real estate data information proofreading and easy data error in the prior art. In order to achieve the above purpose, the technical scheme of the invention is as follows: the real estate data non-corresponding auditing method based on big data comprises the following steps: The method comprises the steps of comparing real estate data information with standard data to determine non-corresponding items, identifying and classifying error items in a data set associated with the non-corresponding items to output processing matters, confirming the non-corresponding items according to the processing matters to generate confirmed items, and verifying the confirmed items based on historical data to output a final confirmed result; wherein, the standard data is determined by the following way: Constructing a comparison data set based on real estate data information and record contents in a preset database; Setting real estate data information as data to be inspected, and setting data items in a comparison data set as initial comparison items; respectively matching the data to be detected with each item in the initial comparison items to output a matching value; and comparing the matching value with a preset matching threshold, if the matching value is larger than the matching threshold, reserving corresponding initial comparison items, and aggregating all reserved initial comparison items to form standard data. Preferably, the real property data information to be verified and the data set associated with the real property data information are acquired before comparing the real property data information with the standard data. Preferably, the real estate data information includes at least one of a equity certificate number, equity name, equity identity number, house seating, house type, house area, and real estate unit number. Preferably, the identifying and classifying the error items in the data set associated with the non-corresponding items includes: Acquiring real estate registration data and property registration data from the associated data set, defining the value of the real estate registration data as a first value and the value of the property registration data as a second value; calculating the ratio of the first value to the second value, and judging whether the ratio is in a preset ratio range; if the ratio is within the preset ratio range, identifying the real estate registration data as first calibration data, and marking the re