Shanghai address database dynamic updating operation system and method

Abstract

The invention relates to the technical field of urban data operation, in particular to a Shanghai address database dynamic updating operation method, which comprises the following steps of: uniformly processing data formats by completing docking with data source interfaces of Shanghai public security, postal service and maps; existing address data in Shanghai are disassembled into hierarchical fields of cities, districts, streets, roads and roadways according to a 18-level structured model, hierarchical differences between a new data source and a golden address library are continuously compared, address change authenticity is inferred through a knowledge graph and a graph neural network, target addresses which are not inquired in continuous 3 months are judged as suspected discarding, and discarding of the target addresses is judged. And predicting a discarding probability and a change state in combination with a time sequence model, and archiving historical data to obtain a complete address library containing a life cycle. According to the method, the problems that the efficiency is low and intelligent, efficient and traceable address library dynamic updating operation cannot be realized when a traditional regular full-quantity synchronization mode is used for dealing with high-frequency address change of an ultra-large city in Shanghai are solved.

Description

Technical Field

[0001] This invention belongs to the field of urban data operation technology, specifically relating to a dynamic update operation system and method for the Shanghai address database. Background Technology

[0002] In today's rapidly developing digital age, the construction and application of address databases play a crucial role in many fields, such as logistics and distribution, urban planning, and public services. However, once the address database is built, it faces a core challenge—the problem of continuous data aging.

[0003] In real-world scenarios, address changes are extremely frequent. This encompasses a variety of situations: the continuous emergence of new residential areas adds new living spaces to the city; the demolition and reconstruction of old districts renews the urban landscape; street name changes are made, either to optimize urban planning or for cultural heritage considerations; administrative division adjustments involve changes at different levels, from 1 to 4; and even building unit numbers are renumbered. These changes keep address information in a dynamic state, posing significant challenges to the maintenance and updating of address databases. Taking Shanghai as an example, as a megacity, the changes in Pudong New Area and Huangpu District, such as the demolition and reconstruction of old neighborhoods (e.g., the renovation of old neighborhoods around Yu Garden in Huangpu District), the construction of new urban areas (e.g., the new residential clusters in the Lingang New Area), and the optimization of street names (e.g., the renaming of some branch roads in industrial parks), are particularly prominent.

[0004] Traditional data maintenance employs a periodic full-data synchronization model, which is extremely inefficient and resource-intensive, making it unsuitable for the needs of cities like Shanghai with high frequency of changes. More importantly, simply deleting old records loses their historical query value—for example, in Shanghai's historical order logistics tracing, deleting old addresses would render the logistics data of merchants around the Bund in the past unverifiable. Therefore, there is an urgent need for a smart, efficient, and traceable address database dynamic update and operation solution that is adaptable to Shanghai's complex address change scenarios and can be quickly replicated nationwide. Summary of the Invention

[0005] To address the aforementioned issues, this invention provides a dynamic update and operation system and method for the Shanghai address database. This system solves the problems of low efficiency and high resource consumption associated with traditional periodic full synchronization methods when dealing with frequent address changes in a megacity like Shanghai. Furthermore, it addresses the loss of historical query value due to simple deletion of old records, failing to achieve intelligent, efficient, and traceable dynamic update and operation of the address database. To achieve the above objectives, this invention adopts the following technical solution: The method for dynamically updating and operating the Shanghai address database includes the following steps: First, by connecting with data source interfaces of Shanghai Public Security Bureau, Post Office, and Maps, the data format is standardized and processed uniformly. Multi-source heterogeneous address information is extracted to obtain standardized access data. Second, existing Shanghai address data is decomposed into city, district, and street / alley level fields according to an 18-level structured model. This is then automatically extracted and mapped to obtain initial data for the authoritative golden address database. Third, the hierarchical differences between new data sources and the golden address database are continuously compared. The authenticity of address changes is inferred using knowledge graphs and graph neural networks. The focus and type of changes are extracted to obtain a precise update task list. Fourth, batch updates, incremental fusion, and lifecycle status change processes are automatically triggered based on the change type. Update operations are executed through the core processing engine to obtain real-time updated golden address database data. Fifth, addresses that have not been found for three consecutive months are judged as potentially abandoned. The abandonment probability is predicted using a time-series model, and the status is changed. Historical data is archived to obtain a complete address database containing the lifecycle.

[0006] Furthermore, by completing the data source interface connection with Shanghai Public Security Bureau, Post Office, and Maps, the data format is uniformly processed, and multi-source heterogeneous address information is extracted to obtain standardized access data. This includes the following steps: adopting a standardized data interface protocol, completing the data source interface connection with Shanghai Public Security Bureau's population database, Shanghai Post Office's delivery database, and Gaode Maps' Shanghai regional data to ensure real-time access of multi-source data; uniformly parsing the accessed heterogeneous data into an internal standard format, extracting the core field information of city, district, street, and house number from the address; and removing invalid and duplicate records through data cleaning and deduplication to obtain standardized access data with a clear structure and uniform format.

[0007] Furthermore, the process of decomposing existing Shanghai address data into city, district, street / alley level fields according to an 18-level structured model, and obtaining authoritative initial data for the golden address database through automated extraction and mapping, includes the following steps: Using the designed 18-level structured address model, existing Shanghai address data is decomposed level by level; using data decomposition tools, core field information of city, district, street / alley, community, and building is automatically extracted from the addresses; based on the mapping relationship defined in the model, the decomposed fields are accurately assigned to their corresponding levels; the extraction results are verified, and abnormal data is corrected to ensure the integrity of the levels and the accuracy of the fields; the processed data is stored in the golden address database to obtain authoritative initial data with a standardized structure and complete fields.

[0008] Furthermore, the continuous comparison of hierarchical differences between new data sources and the golden address database, and the inference of address change authenticity through knowledge graphs and graph neural networks to extract change focus and type, resulting in a precise update task list, includes the following steps: A continuous monitoring mechanism is employed to accurately locate differences by real-time access to multiple new data sources and comparing them item by item with the golden address database at each hierarchical level; an address entity association network is constructed using a knowledge graph, and the change context is analyzed using a graph neural network model to infer and judge the authenticity and logical consistency of address changes; core change types such as administrative division adjustments, road name changes, and building additions / reductions are automatically extracted, clarifying the specific change level and scope; and verified change requests are sorted by priority to obtain a precise update task list including update fields, change types, and processing methods.

[0009] Furthermore, the process of automatically triggering batch updates, incremental fusion, and lifecycle status changes based on the type of change, and executing update operations through the core processing engine to obtain real-time updated data in the golden address database, includes the following steps: An intelligent process scheduling mechanism is adopted to automatically trigger corresponding processing flows by identifying the type of change. Administrative division adjustments trigger the batch update engine to quickly replace affected fields; adding new building units triggers the incremental fusion engine to perform deduplication and field mapping; address obsolescence triggers the lifecycle engine to change the status and archive historical data; the core processing engine automatically selects a low-resource-consumption update strategy according to preset rules, performs data verification and relationship reasoning, and writes the processed data into the golden address database in real time, obtaining dynamically updated data that includes change records and accurate status.

[0010] Furthermore, the process of identifying addresses that have not been queried for three consecutive months as potentially abandoned, predicting the abandonment probability using a time-series model, changing the status, and archiving historical data to obtain a complete address database containing the lifecycle includes the following steps: Using a multi-source data continuous monitoring mechanism, by comparing data sources from Shanghai Public Security Bureau, Post Office, and Maps, target addresses that have not been queried for three consecutive months are extracted as potentially abandoned objects; combining a time-series model to analyze the historical frequency of address changes and urban planning index characteristics, the future abandonment probability is predicted, and the lifecycle status of addresses with probabilities exceeding the threshold is automatically changed to abandoned, with the abandonment date and reason recorded simultaneously; historical data and the current status are integrated and archived, and processed through a lifecycle engine to obtain a dynamic address database containing the complete lifecycle trajectory.

[0011] The second aspect of this invention provides a dynamic update and operation system for the Shanghai address database. This system includes the following modules: a data source interface module, used to connect with data source interfaces of Shanghai Public Security Bureau, Post Office, and Map Bureau to unify data formats, extract multi-source heterogeneous address information, and obtain standardized access data; a data initialization module, used to decompose existing Shanghai address data into city, district, and street / lane level fields according to an 18-level structured model, and obtain initial data for the authoritative golden address database through automated extraction and mapping; a change monitoring module, used to continuously compare the hierarchical differences between new data sources and the golden address database, infer the authenticity of address changes through knowledge graphs and graph neural networks, extract change focus and type, and obtain a precise update task list; a dynamic update module, used to automatically trigger batch updates, incremental fusion, and lifecycle status change processes according to change type, execute update operations through the core processing engine, and obtain real-time updated golden address database data; and an abandoned address determination module, used to determine addresses that have not been found for three consecutive months as suspected abandoned addresses, predict the abandonment probability and change status using a time-series model, archive historical data, and obtain a complete address database containing the lifecycle.

[0012] A third aspect of the present invention provides a Shanghai address database dynamic update operation device, the Shanghai address database dynamic update operation device including a memory and at least one processor, the memory storing instructions; the at least one processor calls the instructions in the memory to cause the Shanghai address database dynamic update operation device to perform the steps of the Shanghai address database dynamic update operation method as described in any of the preceding claims.

[0013] A fourth aspect of the present invention provides a computer-readable storage medium storing instructions, characterized in that, when executed by a processor, the instructions implement the steps of the Shanghai address database dynamic update operation method as described in any one of the preceding claims.

[0014] In the technical solution provided by this invention, by completing the data source interface connection with Shanghai Public Security Bureau, Post Office, and Map Bureau, the data format is uniformly processed, multi-source heterogeneous address information is extracted, and standardized access data is obtained. Existing Shanghai address data is decomposed into city, district, street / lane level fields according to an 18-level structured model. Through automated extraction and mapping, initial data for an authoritative golden address database is obtained. The hierarchical differences between the new data source and the golden address database are continuously compared. The authenticity of address changes is inferred through knowledge graphs and graph neural networks, and the focus and type of changes are extracted to obtain a precise update task list. Based on the change type, batch updates, incremental fusion, and lifecycle status change processes are automatically triggered. The core processing engine executes the update operation to obtain real-time updated golden address database data. Addresses that have not been queried for three consecutive months are judged as suspected abandoned. The abandonment probability is predicted using a time-series model, and the status is changed. Historical data is archived to obtain a complete address database containing the lifecycle. This invention solves the problems of low efficiency, high resource consumption, and loss of historical query value caused by simply deleting old records when dealing with high-frequency address changes in a megacity like Shanghai, which cannot achieve intelligent, efficient, and traceable dynamic update and operation of the address database. Attached Figure Description

[0015] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention.

[0016] Figure 1 This is a schematic diagram of the first embodiment of the Shanghai address database dynamic update operation method in this invention.

[0017] Figure 2 This is a schematic diagram of the second embodiment of the Shanghai address database dynamic update operation method in this invention.

[0018] Figure 3 This is a schematic diagram of the third embodiment of the Shanghai address database dynamic update operation method in this invention.

[0019] Figure 4 This is a schematic diagram of the fourth embodiment of the Shanghai address database dynamic update operation method in this invention.

[0020] Figure 5 This is a schematic diagram of the fifth embodiment of the Shanghai address database dynamic update operation method in this invention. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0022] Those skilled in the art will understand that, unless specifically stated otherwise, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. It should be further understood that the term “comprising” as used in this specification means the presence of the stated features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0023] Shanghai address database dynamic update operation method, such as Figure 1 As shown, the process includes the following steps: First, by connecting with data source interfaces from Shanghai Public Security Bureau, Post Office, and Maps, the data format is standardized, multi-source heterogeneous address information is extracted, and standardized access data is obtained. Second, existing Shanghai address data is decomposed into city, district, and street / alley level fields according to an 18-level structured model. This is then automatically extracted and mapped to obtain the initial data for the authoritative golden address database. Third, the hierarchical differences between the new data source and the golden address database are continuously compared. Knowledge graphs and graph neural networks are used to infer the authenticity of address changes, extracting the focus and type of changes to obtain a precise update task list. Fourth, based on the type of change, batch updates, incremental fusion, and lifecycle status change processes are automatically triggered. The core processing engine executes the update operations to obtain real-time updated golden address database data. Fifth, addresses that have not been found for three consecutive months are judged as suspected abandoned addresses. The abandonment probability is predicted using a time-series model, and the status is changed. Historical data is archived to obtain a complete address database containing the lifecycle.

[0024] In this embodiment, a standardized data interface protocol is adopted. By completing the data source interface connection with the Shanghai Public Security Population Database, Shanghai Postal Delivery Database, and Gaode Map Shanghai Regional Data, the real-time access of multi-source data is ensured. The heterogeneous data is uniformly parsed into an internal standard format, and the core field information of city, district, street, and house number in the address is extracted. Through data cleaning and deduplication, invalid and duplicate records are removed to obtain standardized access data with a clear structure and uniform format.

[0025] In this embodiment, an 18-level structured address model is designed to decompose existing Shanghai address data hierarchically. Through data decomposition tools, core field information of city, district, street, community, and building is automatically extracted from the address. Based on the mapping relationship defined in the model, the decomposed fields are accurately assigned to the corresponding levels, the extraction results are verified, and abnormal data is corrected to ensure the integrity of the hierarchy and the accuracy of the fields. The processed data is stored in the Golden Address Database to obtain authoritative initial data with standardized structure and complete fields.

[0026] Taking Shanghai addresses as an example, the hierarchical mapping relationship is clearly defined. When copying nationwide, only the corresponding administrative division level needs to be matched: Hierarchical numbering Field Name Core Uses Shanghai template example Nationwide adaptation logic ^1-^4 City, district, street, community / village Administrative Management: The Focus of Changes Triggering Batch Update Processes Shanghai (^1) - Pudong New Area (^2) - Zhangjiang High-Tech Park (^3) - Keyuan Community (^4) Municipalities (^1) - Districts (^2) / Provinces (^1) - Cities (^2), subsequent levels are unified ^6-^7 Natural village, village number Suburban Anchor Points: Reference Points for Suburban Address Lifecycle Management Group 3 (6) of Xinqiao Village, Chenjia Town, Chongming District, Shanghai Nationwide unified mapping of suburban / rural areas to corresponding levels ^8-^9 Streets, lanes, and alleys Routing information layer: the focus of naming changes such as road name alteration and lane number merging. Keyuan Road (^8) - Lane 12 (^9) Street, alley, and lane number information from various regions is directly adapted to this level. ^13 courtyard Business naming anchors: the focus of alias change monitoring Zhangjiang Science City Innovation Institute (^13) The naming of commercial compounds and industrial parks nationwide will be uniformly incorporated into this level. ^14-^17 Building, Unit, Floor, Room Physical location layer: the focus of incremental updates such as new buildings and unit reorganization. Building 1 (^14) - Unit 2 (^15) - 5th Floor (^16) - Room 502 (^17) All residential and commercial buildings nationwide will be uniformly divided according to this level. ^18 Other information State storage: Used to store newly added lifecycle states. Lifecycle status: Active / Deprecated, etc. The national address system will adopt the same state storage rule.

[0027] In this embodiment, a continuous monitoring mechanism is adopted. By accessing new data sources from multiple sources in real time and comparing them with the golden address database item by item at each level, the differences are accurately located. A knowledge graph is used to construct an address entity association network, and a graph neural network model is used to analyze the context of changes and infer the authenticity and logical consistency of address changes. The core change types of administrative division adjustments, road name changes, and building additions and subtractions are automatically extracted to clarify the specific change levels and scope. The verified change requests are sorted by priority to obtain a precise update task list that includes the updated fields, change types, and processing methods.

[0028] Change hierarchy and process mapping Change level focus Definition of change type Triggered update process Shanghai Case Example ^1-^4 (Administrative Divisions) R_gold's ^3 (street) name change (e.g., Shanghai's "Zhangjiang Town" renamed to "Zhangjiang High-Tech Park Street") Batch update process: Low-cost replacement of only relevant fields. The system automatically updated "XX Community, Zhangjiang Town, Pudong New Area, Shanghai" to "XX Community, Zhangjiang High-Tech Park Street, Pudong New Area, Shanghai" in batches. ^8 or ^9 (routing information) The street names / alley numbers in R_gold are replaced by the new data source S_new (e.g., "Keyuan Branch Road" in Shanghai is renamed "Innovation Avenue"). Naming change process: Trigger the dual anchoring fusion of patent 1 to update the main name and alias. The original name "Keyuan Branch Road" will be retained as an alias, while the main name will be updated to "Innovation Avenue" to ensure compatibility with historical queries. ^14-^17 (Unit Information) A large number of new ^17 (room) or ^14 (building) records were found under R_gold (e.g., 3 new buildings were built in a talent apartment complex in Lingang New Area, Shanghai). Incremental inbound process: Quickly execute incremental fusion to ensure new addresses are online in a timely manner. Within one week, the addresses of over 500 rooms in three buildings were entered into the database, supporting applications such as express delivery and government registration.

[0029] In this embodiment, an intelligent process scheduling mechanism is adopted. By identifying the type of change, the corresponding processing process is automatically triggered. Administrative division adjustment triggers the batch update engine to quickly replace the affected fields; adding a building unit triggers the incremental fusion engine to perform deduplication and field mapping; address abandonment triggers the lifecycle engine to change the status and archive historical data; the core processing engine automatically selects the update strategy with low resource consumption according to preset rules, performs data verification and relationship reasoning, and writes the processed data into the golden address database in real time to obtain dynamic updated data that includes change records and accurate status.

[0030] Introduce a lifecycle status field (as a subfield of ^18 "Other Information") for address entities, specifying the status application in the Shanghai address scenario: Active: Currently valid address record (e.g., No. 199, Huaihai Middle Road, Xuhui District, Shanghai). Planned: Addresses that are planned but not yet implemented (e.g., "No. 2000, Hongqiao Road" in the Shanghai Hongqiao International Central Business District plan). Deprecated: Addresses no longer used for mailing or location services due to demolition, merger, etc. (e.g., a demolished address in an old alleyway in Huangpu District, Shanghai; not deleted, only marked).

[0031] By monitoring the hierarchical differences between the Shanghai multi-source data source (S_new) and the existing gold records (R_gold), a precise update process is triggered, and this mechanism is directly reused during nationwide replication. An innovative address change inference scheme based on Knowledge Graph (KG) and Graph Neural Network (GNN) is adopted. The technical solution is as follows: 1. Knowledge Graph Construction: The gold address database (R_gold) is modeled as a knowledge graph. Nodes include ^2 districts, ^8 roads, ^9 lanes, ^13 courtyards, etc. Edges represent relationships such as "belonging to", "near", and "aliased". 2. Change Detection and Inference: When new data (S_new) reports a change (e.g., the ^9 lane number changes from "18 lane" to "20 lane"), the system uses a Graph Neural Network (GNN) algorithm (such as GraphSAGE or GAT) to perform relational inference on the graph. The GNN model learns the global contextual relationships of address entities and predicts whether the change conforms to the logical consistency of the graph. 3. Decision: The GNN model predicts the probability of the change. If a change violates known strong correlations in the graph (e.g., the new alley number is inconsistent with the routing information of adjacent ^8 nodes), it is judged as a data error, triggering dynamic error correction in Innovation Point 2. If the GNN model confirms that the change conforms to the evolution trend of neighboring nodes, it is judged as a real physical change, triggering an update. When a new ^17 (room) unit is added to the database, the GNN model is used to learn the characteristics of neighboring addresses to predict the best belonging node to the new unit, either ^9, ^13, or ^14, significantly improving the automation of incremental updates.

[0032] This invention solves the problem of high-dimensional discrimination of address changes. The system no longer relies solely on simple field comparison, but instead uses the global context relationship of address entities to intelligently verify the authenticity of the change.

[0033] By monitoring the hierarchical differences between the Shanghai multi-source data source (S_new) and the existing gold records (R_gold), a precise update process is triggered, and this mechanism is directly reused during nationwide replication. An innovative address change inference scheme based on Knowledge Graph (KG) and Graph Neural Network (GNN) is adopted. The technical solution is as follows: 1. Knowledge Graph Construction: The gold address database (R_gold) is modeled as a knowledge graph. Nodes include ^2 districts, ^8 roads, ^9 lanes, ^13 courtyards, etc. Edges represent relationships such as "belonging to", "near", and "aliased". 2. Change Detection and Inference: When new data (S_new) reports a change (e.g., lane number ^9 changes from "lane 18" to "lane 20"), the system uses a Graph Neural Network (GNN) algorithm (such as GraphSAGE or GAT) to perform relational inference on the graph. The GNN model learns the global contextual relationships of address entities and predicts whether the change conforms to the logical consistency of the graph. 3. Decision: The GNN model predicts the probability of the change. If a change violates known strong correlations in the graph (e.g., the new alley number is inconsistent with the routing information of the adjacent ^8), it is judged as a data error, triggering dynamic error correction in Innovation Point 2. If the GNN model confirms that the change conforms to the evolution trend of neighboring nodes, it is judged as a real physical change, triggering an update. When a new ^17 (room) unit is added to the database, the GNN model is used to learn the characteristics of neighboring addresses to predict the best home node for the new unit, either ^9, ^13, or ^14, significantly improving the automation of incremental updates.

[0034] This invention solves the problem of high-dimensional discrimination of address changes. The system no longer relies solely on simple field comparison, but instead uses the global context relationship of address entities to intelligently verify the authenticity of the change.

[0035] In this embodiment, a multi-source data continuous monitoring mechanism is adopted. By comparing data sources from Shanghai Public Security Bureau, Post Office, and Maps, target addresses that have not been queried for three consecutive months are extracted as suspected abandoned objects. Combining time series model analysis of address historical change frequency and urban planning index characteristics, the probability of future abandonment is predicted, and the life cycle status of addresses with a probability exceeding the threshold is automatically changed to abandoned, while simultaneously recording the abandonment date and reason. Historical data and current status are integrated and archived, and processed by the life cycle engine to obtain a dynamic address database containing a complete life cycle trajectory.

[0036] This invention also provides a dynamic update and operation system for the Shanghai address database, comprising the following modules: a data source connection module, used to connect with data source interfaces of Shanghai Public Security Bureau, Post Office, and Map Bureau, to unify data format processing, extract multi-source heterogeneous address information, and obtain standardized access data; a data initialization module, used to decompose existing Shanghai address data into hierarchical fields of city, district, street, and alley according to an 18-level structured model, and obtain the initial data of the authoritative golden address database through automated extraction and mapping; a change monitoring module, used to continuously compare the hierarchical differences between new data sources and the golden address database, infer the authenticity of address changes through knowledge graphs and graph neural networks, extract the focus and type of changes, and obtain a precise update task list; a dynamic update module, used to automatically trigger batch updates, incremental fusion, and lifecycle status change processes according to the change type, and execute update operations through the core processing engine to obtain real-time updated golden address database data; and an abandoned address determination module, used to determine that addresses that have not been queried for three consecutive months are suspected of being abandoned, combine time series models to predict the abandonment probability and change status, archive historical data, and obtain a complete address database containing the lifecycle.

[0037] The beneficial effects of this invention are: 1. High efficiency: Taking the pilot data in Shanghai as an example, the hierarchical change trigger mechanism improves the update efficiency by 80%, avoiding the waste of resources in full synchronization. This efficiency improvement can be transferred to the whole country.

[0038] 2. Traceability: Solves the problem of data value loss caused by the deletion of old addresses in Shanghai and cities across the country, fully preserves historical address links, and supports historical queries in multiple scenarios such as logistics, taxation, and government affairs.

[0039] 3. Accuracy and replicability: In the Shanghai pilot program, the delay in adding new addresses to the database is ≤7 days, and the delay in updating road name changes is ≤24 hours; the standardized architecture and process can be quickly replicated nationwide, adapting to the address change characteristics of cities of different sizes.

[0040] 4. Adaptability: The hierarchical model designed specifically for the characteristics of Shanghai Municipality (^1 for city, ^2 for district) can be seamlessly adapted to the conventional hierarchical structure of provinces-municipalities-districts-streets across the country without the need for system reconstruction.

[0041] This invention also provides a dynamic update operation device for the Shanghai address database. This device may further include one or more power supplies, one or more wired or wireless network interfaces, one or more input / output interfaces, and / or one or more operating systems, such as Windows Server, MacOSX, Unix, Linux, FreeBSD, etc. Those skilled in the art will understand that the structure of the dynamic update operation device for the Shanghai address database does not constitute a limitation on the computer device provided by this invention, and may include more or fewer components than shown in the figures, or combine certain components, or have different component arrangements.

[0042] The present invention also provides a computer-readable storage medium, which can be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. The computer-readable storage medium stores instructions that, when executed on a computer, cause the computer to perform the various steps of the Shanghai address database dynamic update operation method provided in the above embodiments.

[0043] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely preferred examples and are not intended to limit the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for dynamically updating and operating the Shanghai address database, characterized in that: The method for dynamically updating and operating the Shanghai address database includes the following steps: By completing the data source interface connection with Shanghai Public Security Bureau, Post Office, and Map Bureau, the data format is uniformly processed, multi-source heterogeneous address information is extracted, and standardized access data is obtained. The existing address data in Shanghai is broken down into city, district, street and alley level fields according to an 18-level structured model. Through automated extraction and mapping, the initial data of the authoritative golden address database is obtained. By continuously comparing the hierarchical differences between new data sources and the golden address database, and by reasoning about the authenticity of address changes through knowledge graphs and graph neural networks, the focus and type of changes are extracted to obtain an accurate list of updated tasks. Based on the type of change, batch update, incremental fusion, and lifecycle status change processes are automatically triggered. The update operation is executed through the core processing engine to obtain real-time updated gold address library data. If a target address cannot be found for three consecutive months, it is considered a suspected abandoned address. The abandonment probability is predicted by combining time series models, the status is changed, and historical data is archived to obtain a complete address database containing the life cycle.

2. The method for dynamically updating and operating the Shanghai address database according to claim 1, characterized in that, The process involves establishing data source interfaces with Shanghai Public Security Bureau, Post Office, and Maps Bureau to unify data formats, extract heterogeneous address information from multiple sources, and obtain standardized access data. This includes the following steps: By adopting a standardized data interface protocol, we have completed the data source interface connection with Shanghai Public Security Population Database, Shanghai Postal Delivery Database and Gaode Map Shanghai Area Data to ensure real-time access to multi-source data; The heterogeneous data received is uniformly parsed into an internal standard format, and the core field information of city, district, street, and house number in the address is extracted. By cleaning and deduplicating data, invalid and duplicate records are removed, resulting in standardized access data with a clear structure and uniform format.

3. The method for dynamically updating and operating the Shanghai address database according to claim 1, characterized in that, The process of breaking down existing Shanghai address data into city, district, and street / alley level fields according to an 18-level structured model, and then automatically extracting and mapping this data to obtain the initial data for the authoritative golden address database, includes the following steps: Using the designed 18-level structured address model, the existing address data in Shanghai is decomposed level by level. Through data decomposition tools, the core field information of city, district, street, community, and building in the address is automatically extracted. Based on the mapping relationship defined in the model, the decomposed fields are accurately assigned to the corresponding levels, the extraction results are verified, and abnormal data is corrected to ensure the integrity of the levels and the accuracy of the fields. The processed data is stored in the Golden Address Database to obtain authoritative initial data with a standardized structure and complete fields.

4. The method for dynamically updating and operating the Shanghai address database according to claim 1, characterized in that, The continuous comparison of the hierarchical differences between the new data source and the golden address database, the inference of address change authenticity through knowledge graphs and graph neural networks, the extraction of change focus and type, and the resulting accurate update task list include the following steps: A continuous monitoring mechanism is adopted to accurately locate differences by real-time access to new data sources from multiple sources and comparing them with the golden address database at each level and field. A knowledge graph is used to construct an address entity association network. A graph neural network model is then used to analyze the context of address changes and to infer the authenticity and logical consistency of address changes. Automatically extract the core change types such as administrative division adjustments, road name changes, and building additions / reductions, and clarify the specific change levels and scope; The verified change requests are sorted by priority to obtain a precise list of update tasks, including the fields to be updated, the type of change, and the processing method.

5. The method for dynamically updating and operating the Shanghai address database according to claim 1, characterized in that, The process of automatically triggering batch updates, incremental fusion, and lifecycle state changes based on the type of change, and executing update operations through the core processing engine to obtain real-time updated gold address database data, includes the following steps: An intelligent process scheduling mechanism is adopted to automatically trigger corresponding processing procedures by identifying the type of change. When administrative division is adjusted, a batch update engine is triggered to quickly replace the affected fields. Adding a new building unit triggers the incremental fusion engine to perform deduplication and field mapping; address obsolescence triggers the lifecycle engine to change the status and archive historical data. The core processing engine automatically selects the update strategy with low resource consumption according to preset rules, performs data verification and relationship reasoning, and writes the processed data into the golden address database in real time, resulting in dynamic update data that includes change records and accurate status.

6. The method for dynamically updating and operating the Shanghai address database according to claim 1, characterized in that, The process of determining a suspected abandoned address based on no target address found for three consecutive months, predicting the abandonment probability using a time-series model, changing the status, and archiving historical data to obtain a complete address database containing the lifecycle includes the following steps: A multi-source data continuous monitoring mechanism is adopted. By comparing data sources from Shanghai Public Security Bureau, Post Office, and Maps, target addresses that have not been queried for three consecutive months are extracted as suspected abandoned objects. By combining time series model analysis of address historical change frequency and urban planning index characteristics, the probability of future abandonment is predicted, and the life cycle status of addresses with a probability exceeding the threshold is automatically changed to abandoned, while simultaneously recording the abandonment date and reason. Historical data is integrated and archived with the current state, and then processed by the lifecycle engine to obtain a dynamic address library containing the complete lifecycle trajectory.

7. The Shanghai address database dynamic update operation system, characterized in that, The Shanghai address database dynamic update operation system includes the following modules: The data source docking module is used to complete the data source interface docking with Shanghai Public Security Bureau, Post Office, and Map Bureau, to unify the data format, extract multi-source heterogeneous address information, and obtain standardized access data. The data initialization module is used to decompose the existing address data in Shanghai into hierarchical fields of city, district, street and alley according to the 18-level structured model. Through automatic extraction and mapping, the initial data of the authoritative golden address database is obtained. The change monitoring module is used to continuously compare the hierarchical differences between the new data source and the golden address database. It uses knowledge graphs and graph neural networks to infer the authenticity of address changes, extract the focus and type of changes, and obtain a precise update task list. The dynamic update module is used to automatically trigger batch updates, incremental fusion, and lifecycle state change processes based on the type of change. It executes update operations through the core processing engine to obtain real-time updated gold address library data. The abandoned address determination module is used to determine that an address that has not been found for three consecutive months is suspected to be abandoned. It combines a time series model to predict the probability of abandonment, changes the status, archives historical data, and obtains a complete address database containing the life cycle.

8. Shanghai address database dynamic update operation equipment, characterized in that, The Shanghai address database dynamic update operation device includes a memory and at least one processor. The memory stores instructions, and the at least one processor invokes the instructions in the memory to cause the Shanghai address database dynamic update operation device to perform each step of the Shanghai address database dynamic update operation method as described in any one of claims 1-6.

9. A computer-readable storage medium storing instructions thereon, characterized in that, When the instructions are executed by the processor, they implement the various steps of the Shanghai address database dynamic update operation method as described in any one of claims 1-6.

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