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

Inactive Publication Date: 2014-08-27
FUDAN UNIV
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Problems solved by technology

[0003] However, the current entity relationship extraction technology is mainly based on the method of iterative search of seed patterns or the method based on natural language processing. What they finally extract is a deterministic relationship description, and this deterministic description is in the

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  • Method and system of relation characterizing, clustering and identifying based on the semanteme of semantic space mapping
  • Method and system of relation characterizing, clustering and identifying based on the semanteme of semantic space mapping
  • Method and system of relation characterizing, clustering and identifying based on the semanteme of semantic space mapping

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Embodiment Construction

[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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Abstract

The invention belongs to the technical field of text semanteme processing, specially refer to a method and a system of relation characterizing, clustering and identifying based on semanteme of semantic space mapping. For the objects of the relationship to be extracted the invention comprises that grammar depending analysis is carried out for the sentence including two objects at first; then the analysis results is regarded as Graph, and the shortest path between two knots related two objects in Graph is calculated, to extract the relation of objects; afterwards, the words in the path is projected to semantic space, to accumulate and to obtain the vector expression of the relation in the semantic space; in the situation of multigroup of object couples, the relations are clustered by clustering method, to structure relatio model; according to semanteme vector expressing relation of input object couples and the semantic similar degree among relation models identification of relation is realized. The invention overcomes the shortcomings of the traditional method,such the sensitive factors as words deformation, synonym change, grammatical form changes etc. The accuracy and processing flexibility of identifying relationship is improved.

Description

technical field [0001] The invention belongs to the technical field of text semantic information processing, and in particular relates to a semantic relationship representation, clustering and recognition method and system based on semantic space mapping. Background technique [0002] With the popularization of computers and the development of network technology, all kinds of massive data are presented in the form of electronic text. How to extract the semantic information that users care about is very important. In addition to entity extraction, users tend to pay more attention to the relationship between entities. What is the semantic relationship, because the semantic relationship truly reflects the essence of data interconnection and organically combines the complex entity world. It has important application value in many fields: for example, in information retrieval systems, entity relationship extraction Technology makes it possible to realize semantic retrieval functi...

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Application Information

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IPC IPC(8): G06F17/27G06F17/30
Inventor 王晓平肖仰华汪卫
Owner FUDAN UNIV
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