A Multi-source Heterogeneous Data Fusion Method Based on Geographic Entity

Abstract

A function that can realize semantic search, multi-dimensional query, association analysis, knowledge reasoning and other functions of geographical knowledge, and can realize custom connection of business data and dynamic connection of IoT perception information in the structured management of geographic entities, and realize multi-source heterogeneity Data fusion, so as to provide scientific decision-making support for intelligent construction. The method of multi-source heterogeneous data fusion, including extracting the geographical entity space-time knowledge map, and combining the extracted geographical entity space-time knowledge map with multiple external knowledge maps. , the step of forming a complete geographical knowledge map.

Description

technical field [0001] The invention relates to a multi-source heterogeneous data fusion method, in particular to a multi-source heterogeneous data fusion method based on the structured management of geographic entities. Background technique [0002] With the development of intelligent cities, digital twinning is an effective way of intelligent urbanization, and the construction of a real-world 3D spatial information platform is the basis for the accurate mapping and integration and collaboration of the twin geographic entities in the physical space and information space throughout the life cycle, and is also the basis for geographic entities. Reflection of the level of structured management informatization. City Information Modeling (CIM) is a digital representation and description of various physical objects and spatial and temporal states on the ground, underground, indoors and outdoors, which reflects urban planning, construction, development and operation. [0003] The...

AI Technical Summary

Problems solved by technology

Use a dynamically expandable semantic template library to realize semantic mapping between multi-source heterogeneous data sources, generate semantic dictionaries, realize semantic cleaning rules can be defined, ensure that text data can be automatically converted semantically between heterogeneous data sources, and realize text data Intelligent cleaning and transaction. This technology realizes automatic semantic conversion and transaction of unstructured multi-source heterogeneous data. It cannot realize custom connection of business data and dynamic connection of IoT perception information in structured management, and realize multi-source heterogeneity. Data Fusion

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