Real estate address processing method and device

Abstract

The invention provides a real estate address processing method and device, and the method comprises the steps: inputting the input real estate address information into a recognition model for semantic analysis processing, and obtaining a plurality of word segmentation results; filtering the plurality of word segmentation results, and taking the segmented words related to the geographic information as key geographic information; comparing the key geographic information with records in a preset special residence database, and searching whether a matched target special residence address exists or not; the special residence database comprises each special residence address and a corresponding tax calculation rule; and if the target special residence address is found, the tax calculation logic is automatically adjusted according to the tax calculation rule corresponding to the target special residence address so as to calculate the transaction tax, so that the accuracy of tax calculation is improved, the requirement of manual calculation can be reduced, and the calculation efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a method and device for processing a real estate address. Background Art

[0002] Tax actuarial calculation is an important part of second-hand real estate transactions, which involves the accurate calculation and collection of taxes during the transaction process. Since real estate transactions involve a wide variety of taxes and fees and complex calculation rules, the accuracy of tax calculation is directly related to the rights and interests of both parties to the transaction and the smooth completion of the transaction. Inaccurate tax calculation may lead to additional financial burdens and even legal disputes.

[0003] With the development of the real estate market and the continuous changes in tax policies, the difficulty of tax actuarial calculation is also increasing. Traditional tax actuarial calculation relies on manual calculation, which is not only inefficient but also prone to errors. In addition, the tax calculation rules for special residences such as affordable housing and economically affordable housing are different from those for ordinary residences, requiring more refined management. Therefore, how to improve the efficiency and accuracy of tax actuarial calculation has become an urgent problem to be solved in the field of real estate transactions. Summary of the invention

[0004] The present invention provides a method and device for processing a real estate address, which are used to solve the defects of inaccurate and low efficiency calculation of transaction taxes and fees in the prior art.

[0005] The present invention provides a method for processing a real estate address, comprising: Input the input property address information into the recognition model for semantic analysis and processing to obtain multiple word segmentation results; wherein the recognition model is trained by the property address samples and the word segmentation result samples; Filter multiple word segmentation results and use the word segmentation related to geographic information as key geographic information; Compare the key geographic information with records in a preset special residential database to find out whether there is a matching target special residential address; the special residential database includes each special residential address and corresponding tax calculation rules; If the target special residential address is found, the tax calculation logic is automatically adjusted according to the tax calculation rules corresponding to the target special residential address to calculate the transaction tax.

[0006] According to the method for processing the real estate address provided by the present invention, the key geographic information is compared with the records in the preset special residential database to find out whether there is a matching target special residential address, including: Compare each key geographic information with the records in the preset special residential database to find out whether there is a matching special residential address; If there are multiple matching special residential addresses, the multiple matching special residential addresses are further compared with the property address information to find out whether there is a matching target special residential address; If there is a matching special residential address, the special residential address is used as the target special residential address.

[0007] According to the method for processing real estate addresses provided by the present invention, the multiple matching special residential addresses are further compared with the real estate address information to find out whether there is a matching target special residential address, which specifically includes: using the key geographic information as a prompt word, continuing to input the multiple matching special residential addresses into the recognition model, and continuing to compare them with the real estate address information to find out whether there is a target special residential address that matches the real estate address information.

[0008] According to the method for processing real estate addresses provided by the present invention, after searching whether there is a matching target special residential address, the method further includes: if the target special residential address is not found, the real estate address information is used as an ordinary residence, and the transaction tax is calculated according to the tax calculation rules corresponding to the ordinary residence.

[0009] According to the method for processing real estate addresses provided by the present invention, the key geographic information includes at least one item: city information, district information, street information, community information, building number information, and unit information.

[0010] According to the method for processing property addresses provided by the present invention, the special residential database further includes: the house type corresponding to each special residential address, the house type including ordinary residence, affordable housing, apartment or shop; The key geographic information is compared with the records in the preset special residential database to find out whether there is a matching target special residential address, specifically including: determining the house type of the input property address information; comparing the key geographic information and the house type with the records in the preset special residential database to find out whether there is a matching target special residential address.

[0011] The present invention also provides a real estate address processing device, comprising: An analysis module is used to input the input real estate address information into a recognition model for semantic analysis and processing to obtain multiple word segmentation results; wherein the recognition model is trained by real estate address samples and word segmentation result samples; A filtering module is used to filter multiple segmentation results and use segmentations related to geographic information as key geographic information; An information comparison module is used to compare the key geographic information with records in a preset special residential database to find out whether there is a matching target special residential address; the special residential database includes each special residential address and corresponding tax calculation rules; The tax calculation module is used to automatically adjust the tax calculation logic according to the tax calculation rules corresponding to the target special residential address if the target special residential address is found, so as to calculate the transaction tax.

[0012] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, a method for processing a property address as described above is implemented.

[0013] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the method for processing a property address as described in any one of the above is implemented.

[0014] The present invention also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements any of the above-mentioned methods for processing a property address.

[0015] The present invention also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements any of the above-mentioned methods for processing a property address.

[0016] The method and device for processing real estate addresses provided by the present invention identify the tax calculation logic of real estate transactions through automated semantic analysis and database matching. If the real estate address information corresponds to a special residence, the tax calculation logic can be automatically adjusted to calculate taxes, thereby not only helping to improve the accuracy of tax calculations, but also reducing the need for manual calculations and improving calculation efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 This is one of the flow charts of the method for processing a real estate address provided by the present invention.

[0019] Figure 2 This is the second flow chart of the method for processing a real estate address provided by the present invention.

[0020] Figure 3 This is the third flow chart of the method for processing a real estate address provided by the present invention.

[0021] Figure 4 It is a structural schematic diagram of a real estate address processing device provided by the present invention.

[0022] Figure 5 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0023] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0024] In order to solve the technical defects of inaccurate and inefficient calculation of transaction taxes and fees in the prior art, improve the accuracy of tax and fee calculation, reduce the need for manual calculation, and improve calculation efficiency, the embodiment of the present invention discloses a method for processing a real estate address, see Figure 1 ,include: 101. Input the input real estate address information into a recognition model for semantic analysis and processing to obtain multiple word segmentation results; wherein the recognition model is trained by real estate address samples and word segmentation result samples.

[0025] In this embodiment, the recognition model is a core component used to perform semantic analysis on the input property address information to extract key geographic information. This model can be of the following types: Natural Language Processing (NLP) Model: Using NLP technology, the model can identify and understand patterns in human language, thereby effectively segmenting address text and extracting key information.

[0026] Machine learning model: By training and learning the characteristics of address data, the model can recognize and classify address information. This may include algorithms such as decision trees, support vector machines (SVM), random forests, etc.

[0027] Deep learning models: Use neural networks, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), or long short-term memory networks (LSTMs) to perform more complex semantic analysis and pattern recognition.

[0028] The input property address information is input into the recognition model for semantic analysis and processing. The process of obtaining multiple word segmentation results can be expanded into the following steps: Data preprocessing: Before entering the property address information, perform data cleaning to remove irrelevant characters such as special symbols, extra spaces, etc.

[0029] Word segmentation: Use word segmentation algorithms to break down address text into smaller units, such as words or phrases.

[0030] Part-of-speech tagging: Tag the word segmentation results to identify the part of speech of each word, such as noun, verb, adjective, etc.

[0031] Named Entity Recognition (NER): Identify named entities in word segmentation results, especially entities related to geographic information, such as places, organization names, etc.

[0032] 102. Filter multiple word segmentation results and use the word segmentations related to geographic information as key geographic information.

[0033] In this embodiment, the execution subject may be a transaction tax calculation system running on a terminal. The system may provide a clear operation interface for users, allowing them to input property address information and display tax calculation results; at the same time, the system may record the results of each matching attempt and continuously optimize the matching algorithm.

[0034] The key geographic information includes at least one of: city information, district information, street information, community information, building number information, and unit information.

[0035] For example, the property address information "No. 1, Building 2, Unit 3, 101, No. 1, Second East Road, First Street, Haidian District, Beijing" is decomposed into "Beijing City", "Haidian District", "First Street", "No. 1, Second East Road", "Building 2", "Unit 3", "101", etc. Among them, the tax calculation does not depend on the specific room number "101", so this information will not be used as key geographic information.

[0036] 103. Compare the key geographic information with the records in a preset special residential database to find out whether there is a matching target special residential address; the residential database includes each special residential address and the corresponding tax calculation rules.

[0037] In the system of this embodiment, a database containing detailed information of various special residences needs to be established and maintained in advance, covering all known special residence addresses, tax calculation rules, etc. The system can regularly update the special residence database to reflect the latest tax policy changes.

[0038] Special housing usually refers to those types of properties that are different from ordinary housing in terms of tax calculation, property rights, transaction rules, etc. For example, special housing includes government-provided affordable housing, such as affordable housing, price-limited housing, public rental housing, etc. Its transactions may need to follow specific rules, such as approval by relevant government departments.

[0039] The system checks whether each key geographic information element matches a record in the database. For example, the system may find that "No. 1 Xingfu East Road" is associated with a specific residence in the database.

[0040] 104. If the target special residential address is found, the tax calculation logic is automatically adjusted according to the tax calculation rules corresponding to the target special residential address to calculate the transaction tax.

[0041] Among them, transaction taxes and fees may include deed tax, land value-added tax, surcharge and stamp duty, etc.

[0042] If the system finds a matching special residential address in step 103, it will automatically adjust the tax calculation logic according to the tax calculation rules corresponding to the address. The system will calculate the transaction tax based on the tax rules for special residential properties, such as possible exemptions, tax rates, etc. For example, if "No. 1 Xingfu East Road" is an affordable housing, the system will apply the tax calculation rules for affordable housing.

[0043] Based on the retrieved rules, the system will determine the parameters required to calculate taxes, such as the property transaction price, property area, holding period, whether it is the first home, etc. The system will apply the corresponding tax calculation formula based on the determined parameters and rules. For example, if the rules stipulate that the deed tax for special residential properties is 1% of the transaction price, the system will calculate the deed tax amount.

[0044] The method for processing real estate addresses provided in the embodiment of the present invention, through automated semantic analysis and database matching, can automatically adjust the tax calculation logic if the real estate address information corresponds to a special residence, thereby not only helping to improve the accuracy of tax calculations, but also reducing the need for manual calculations and improving calculation efficiency.

[0045] Specifically, a recognition model may be run in the tax calculation system of this embodiment, and the recognition model may perform semantic analysis based on the input property address information to obtain key geographic information, and then compare the key geographic information with the records in a preset special residential database.

[0046] Among them, the recognition model is one of the core components, which is responsible for performing semantic analysis on the input property address information and extracting key geographic information elements.

[0047] The recognition model can be a natural language processing (NLP) model, a machine learning model, or a deep learning model. The input layer of the recognition model receives the original real estate address text information, and the processing layer performs operations such as word segmentation, part-of-speech tagging, and named entity recognition (NER) to identify the various components of the address; the output layer outputs key geographic information elements, such as city, district, street, community name, building number, unit number, etc.

[0048] Specifically, see Figure 2 , step 102 comprises: 201. Compare each key geographic information with the records in the preset special residential database to find out whether there is a matching special residential address.

[0049] The system will accurately match key geographic information elements extracted from property address information, such as "Beijing City", "Haidian District", "Zhongguancun Street", etc., with records in the special residential database.

[0050] In addition, the system can also use a fuzzy matching algorithm to adapt to small errors or variations in address input, thereby improving the flexibility and accuracy of matching.

[0051] 202. If there are multiple matching special residential addresses, the multiple matching special residential addresses are further compared with the property address information to find out whether there is a matching target special residential address.

[0052] Specifically, the system can use the key geographic information as a prompt word, continue to input the multiple matching special residential addresses into the recognition model, and continue to compare them with the real estate address information to find out whether there is a target special residential address that matches the real estate address information.

[0053] If the system finds multiple possible matches for a special residential address, it will use more detailed information, such as community name, building number, unit number, etc., for further comparison.

[0054] And further, the system can introduce user interaction, requesting the user to confirm the best matching address, or provide additional information to help the system make a more accurate match.

[0055] 203. If there is a matching special residential address, use the special residential address as the target special residential address.

[0056] Once the system identifies a unique matching special residential address, it will be marked as the target special residential address and used for subsequent tax calculations. The system can record key geographic information elements used in the matching process to provide transparency in tax calculation reports.

[0057] 204. If the target special residential address is not found, the property address information is treated as an ordinary residence, and the transaction tax is calculated according to the tax calculation rules corresponding to the ordinary residence.

[0058] The system can provide an interface that allows users to review and confirm the tax calculation category (special residential or ordinary residential) after the tax calculation is completed, and provide options for appeal or correction.

[0059] The real estate transaction tax calculation method of this embodiment can be more flexible, accurate and user-friendly, while ensuring the compliance of tax calculation and the security of data.

[0060] On the other hand, the special residential database also includes: the house type corresponding to each special residential address, the house type including ordinary residence, affordable housing, apartment or shop; The key geographic information is compared with the records in the preset special residential database to find out whether there is a matching target special residential address, specifically including: determining the house type of the input property address information; comparing the key geographic information and the house type with the records in the preset special residential database to find out whether there is a matching target special residential address.

[0061] By setting up a special residential database to include house type information, properties can be classified more accurately and the accuracy of tax calculations can be improved.

[0062] In order to facilitate understanding of the solution of this embodiment, a specific example is used as an example to illustrate the present invention. Figure 3 , Figure 3 A schematic diagram of a method for processing a property address according to an embodiment of the present invention is shown, which specifically includes: 301. Receive input property address information.

[0063] The input property address information is "Unit 1, Building 1, 111, No. 1, Huayuan Road, Haidian District, Beijing".

[0064] 302. Input the input property address information into the recognition model for semantic analysis and processing to obtain multiple word segmentation results.

[0065] The word segmentation results obtained may be "Beijing City", "Haidian District", "Huayuan Road", "No. 1 Courtyard", "Huayuan Road A", "No. 1 Courtyard", "No. 1 Building", "Unit 1", and "111".

[0066] 303. Filter the multiple word segmentation results and use the word segmentations related to geographic information as key geographic information.

[0067] Among them, the tax calculation does not depend on the specific room number "111", so this information will not be used as key geographic information.

[0068] 304. Compare each key geographic information with the records in the preset special residential database to find out whether there is a matching special residential address.

[0069] After comparison, the matching special residential addresses "No. 13, Huayuan Road, Haidian District" and "No. 2, Huayuan Road, Haidian District" are returned.

[0070] 305. If there are multiple matching special residential addresses, the key geographic information is used as a prompt word, and the multiple matching special residential addresses are continuously input into the recognition model, and are continuously compared with the real estate address information to find out whether there is a target special residential address that matches the real estate address information.

[0071] Using the key geographic information as prompts, the special residential addresses "No. 13, Huayuan Road, Haidian District" and "No. 2, Huayuan Road, Haidian District" are continuously input into the recognition model.

[0072] Specifically, you can input the question: "No. 13, Huayuan Road, Haidian District", "No. 1, Huayuan Road, Haidian District", and which of the above is the most matched with "No. 1, Huayuan Road, Haidian District, Beijing, No. 1 Building, No. 1 Unit, 111", and output "No. 1, Huayuan Road, Haidian District" to the recognition model. Then calculate according to the tax calculation rules corresponding to the target special residential address "No. 1, Huayuan Road, Haidian District".

[0073] 306. If there is a matching special residential address, use the special residential address as the target special residential address.

[0074] 307. If the target special residential address is not found, the property address information will be treated as an ordinary residence, and the transaction tax will be calculated according to the tax calculation rules corresponding to ordinary residences.

[0075] The method of the embodiment of the present invention can ensure that the tax calculation rules for special residences are correctly applied through precise semantic analysis and database matching, thereby improving the accuracy of tax calculation.

[0076] Secondly, the automated tax calculation method reduces manual intervention and the possibility of human error. It also reduces labor costs and improves overall economic benefits.

[0077] In addition, the system of the embodiment of the present invention may provide a user interface, allowing the user to input a property address and display tax calculation results, thereby improving the convenience of user operation.

[0078] The following is a description of a real estate address processing device provided in an embodiment of the present invention. The real estate address processing device described below and the real estate address processing method described above can correspond to each other.

[0079] The embodiment of the present invention provides a device for processing a real estate address. Figure 4 ,include: The analysis module 401 is used to input the input real estate address information into the recognition model for semantic analysis and obtain multiple word segmentation results; wherein the recognition model is trained by real estate address samples and word segmentation result samples; A filtering module 402 is used to filter the multiple segmentation results and use the segmentations related to geographic information as key geographic information; An information comparison module 403 is used to compare the key geographic information with records in a preset special residential database to find out whether there is a matching target special residential address; the special residential database includes each special residential address and corresponding tax calculation rules; The tax calculation module 404 is used to automatically adjust the tax calculation logic according to the tax calculation rules corresponding to the target special residential address to calculate the transaction tax if the target special residential address is found.

[0080] Optionally, the information comparison module 403 is specifically used to: Compare each key geographic information with the records in the preset special residential database to find out whether there is a matching special residential address; If there are multiple matching special residential addresses, the multiple matching special residential addresses are further compared with the property address information to find out whether there is a matching target special residential address; If there is a matching special residential address, the special residential address is used as the target special residential address.

[0081] Optionally, the information comparison module 403 is specifically used to: use the key geographic information as a prompt word, continue to input the multiple matching special residential addresses into the recognition model, and continue to compare them with the real estate address information to find out whether there is a target special residential address that matches the real estate address information.

[0082] The real estate address processing device provided in the embodiment of the present invention can automatically adjust the tax calculation logic through automated semantic analysis and database matching if the real estate address information corresponds to a special residence, thereby not only helping to improve the accuracy of tax calculation, but also reducing the need for manual calculation and improving calculation efficiency.

[0083] Figure 5An example of a physical structure diagram of an electronic device is shown in FIG. Figure 5 As shown, the electronic device may include: a processor 510, a communication interface 520, a memory 530 and a communication bus 540, wherein the processor 510, the communication interface 520 and the memory 830 communicate with each other through the communication bus 540. The processor 510 may call the logic instructions in the memory 530 to execute the method for processing the real estate address, which includes: inputting the input real estate address information into the recognition model for semantic analysis and processing to obtain multiple word segmentation results; wherein the recognition model is obtained by training the real estate address sample and the word segmentation result sample; filtering the multiple word segmentation results and taking the word segmentation related to the geographic information as the key geographic information; comparing the key geographic information with the records in the preset special residential database to find out whether there is a matching target special residential address; the special residential database includes each special residential address and the corresponding tax calculation rules; if the target special residential address is found, the tax calculation logic is automatically adjusted according to the tax calculation rules corresponding to the target special residential address to calculate the transaction tax.

[0084] In addition, the logic instructions in the above-mentioned memory 530 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0085] On the other hand, the present invention also provides a computer program product, which includes a computer program, which can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the real estate address processing method provided by the above-mentioned methods, the method including: inputting the input real estate address information into a recognition model for semantic analysis processing to obtain multiple word segmentation results; wherein the recognition model is trained by real estate address samples and word segmentation result samples; filtering among the multiple word segmentation results, and taking the word segmentation related to geographic information as key geographic information; comparing the key geographic information with the records in a preset special residential database to find out whether there is a matching target special residential address; the special residential database includes each special residential address and the corresponding tax calculation rules; if the target special residential address is found, the tax calculation logic is automatically adjusted according to the tax calculation rules corresponding to the target special residential address to calculate the transaction tax.

[0086] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the real estate address processing method provided by the above-mentioned methods, the method comprising: inputting the input real estate address information into a recognition model for semantic analysis processing to obtain multiple word segmentation results; wherein the recognition model is trained by real estate address samples and word segmentation result samples; filtering among the multiple word segmentation results, taking the word segmentations related to geographic information as key geographic information; comparing the key geographic information with the records in a preset special residential database to find out whether there is a matching target special residential address; the special residential database includes each special residential address and the corresponding tax calculation rules; if the target special residential address is found, the tax calculation logic is automatically adjusted according to the tax calculation rules corresponding to the target special residential address to calculate the transaction tax.

[0087] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0088] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0089] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention 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. However, 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 invention.

Claims

1. A method for processing a real estate address, characterized in that: include: Input the input property address information into the recognition model for semantic analysis and processing to obtain multiple word segmentation results; wherein the recognition model is trained by the property address samples and the word segmentation result samples; Filter multiple word segmentation results and use the word segmentation related to geographic information as key geographic information; Compare the key geographic information with records in a preset special residential database to find out whether there is a matching target special residential address; the special residential database includes each special residential address and corresponding tax calculation rules; If the target special residential address is found, the tax calculation logic is automatically adjusted according to the tax calculation rules corresponding to the target special residential address to calculate the transaction tax.

2. The method for processing a property address according to claim 1, characterized in that: Compare the key geographic information with the records in the preset special residential database to find out whether there is a matching target special residential address, including: Compare each key geographic information with the records in the preset special residential database to find out whether there is a matching special residential address; If there are multiple matching special residential addresses, the multiple matching special residential addresses are further compared with the property address information to find out whether there is a matching target special residential address; If there is a matching special residential address, the special residential address is used as the target special residential address.

3. The method for processing a property address according to claim 2, characterized in that: The multiple matching special residential addresses are further compared with the property address information to find out whether there is a matching target special residential address, specifically including: Using the key geographic information as a prompt word, the multiple matching special residential addresses are further input into the recognition model, and are further compared with the real estate address information to find out whether there is a target special residential address that matches the real estate address information.

4. The method for processing a property address according to claim 1, characterized in that: After searching for a matching target special residential address, the method further includes: if the target special residential address is not found, treating the property address information as an ordinary residence, and calculating the transaction tax according to the tax calculation rules corresponding to ordinary residences.

5. The method for processing a property address according to claim 1, characterized in that: The key geographic information includes at least one item: city information, district information, street information, community information, building number information, and unit information.

6. The method for processing a property address according to claim 1, characterized in that: The special residential database also includes: the house type corresponding to each special residential address, the house type including ordinary residence, affordable housing, apartment or shop; Compare the key geographic information with the records in the preset special residential database to find out whether there is a matching target special residential address, specifically including: Determine the housing type of the input property address information; The key geographic information and the house type are compared with the records in a preset special residential database to find out whether there is a matching target special residential address.

7. A device for processing a real estate address, characterized in that: include: An analysis module is used to input the input real estate address information into a recognition model for semantic analysis and processing to obtain multiple word segmentation results; wherein the recognition model is trained by real estate address samples and word segmentation result samples; A filtering module is used to filter multiple segmentation results and use segmentations related to geographic information as key geographic information; An information comparison module is used to compare the key geographic information with records in a preset special residential database to find out whether there is a matching target special residential address; the special residential database includes each special residential address and corresponding tax calculation rules; The tax calculation module is used to automatically adjust the tax calculation logic according to the tax calculation rules corresponding to the target special residential address if the target special residential address is found, so as to calculate the transaction tax.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the method for processing the property address as described in any one of claims 1 to 6 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for processing a property address as claimed in any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method for processing a property address as claimed in any one of claims 1 to 6 is implemented.

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