Method and system of relation characterizing, clustering and identifying based on the semanteme of semantic space mapping
A technology of spatial mapping and semantic relationship, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve application requirements such as relationship clustering or identification difficulties, weak robustness, low semantic accuracy, etc. , to facilitate relationship clustering, enhance flexibility, and facilitate relationship identification
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[0051] The following examples are used to demonstrate the specific implementation of the present invention, and each module of the system sequentially processes as follows:
[0052] (1) Entity pair and sentence input
[0053] Enter example sentences:
[0054] "Beijing is the capital of China.".
[0055] (2) Extraction of relationships between entities
[0056] (2.1) Analysis of grammatical dependence
[0057] Use Standford Parser to analyze the grammatical dependencies of the example sentences, and get the following results:
[0058] nsubj(capital-4, Beijing-1)
[0059] cop(capital-4, is-2)
[0060] det(capital-4, the-3)
[0061] root(ROOT-0, capital-4)
[0062] prep_of(capital-4, China-6)
[0063] (2.2) Shortest path calculation
[0064] Regarding the above result as Graph and the analyzed unit as a node in Graph, the Dijkstra algorithm is used to calculate the shortest path between the two nodes of interest "Beijing" and "China", and the following results are obtained:
[0065] Shortest Path: ...
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