Natural language knowledge acquisition method based on semantic matching driving

A technology for semantic matching and knowledge acquisition, applied in special data processing applications, instruments, electrical digital data processing, etc.

Inactive Publication Date: 2013-02-27
ANYANG NORMAL UNIV
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AI Technical Summary

Problems solved by technology

Modality is one of the key factors to describe the state of action execution. The precise semantics of many words in natural language essentially contains the modality of an action concept. It is difficult to accurately describe the semantics of concepts
Ontology can strictly represent the semantics of concepts. Ontologies generally use description logic to represent all concepts; however, in description logic, the semantic relationship between concepts is treated equally, and there is no special semantic explanation for the essential characteristics of the semantic relationship of action concepts and processing

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  • Natural language knowledge acquisition method based on semantic matching driving
  • Natural language knowledge acquisition method based on semantic matching driving
  • Natural language knowledge acquisition method based on semantic matching driving

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Embodiment Construction

[0021] The specific implementation process of the natural language knowledge acquisition method driven by semantic matching in the present invention is as follows:

[0022] step 1:

[0023] (1a) Define the semantic matching relationship between words:

[0024] Definition 1: In the lexical semantic knowledge base, any two content words W X and W Y The intrinsic semantic connection between them is called semantic matching relationship. Use the function match(W X , W Y ) to represent its closeness, and the value of the function is the semantic matching value. The semantic matching relationship has nothing to do with specific sentences. If W X with W Y There is no semantic matching relationship between them, then set match(W X ,W Y )=MAX, MAX is a large constant.

[0025] (1b) Definition 2: Any content word W in the sentence i (except the predicate head word) are semantically modified on another content word W Gi , called W Gi is W i Semantic modification target.

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Abstract

The utility model discloses a natural language knowledge acquisition method based on semantic matching driving. The natural language knowledge acquisition method comprises the following steps: (1) defining a semantic model for natural language processing; (2) defining a representing method of lexical semantic; (3) defining semantic matching relations among the lexicons; (4) defining a processing method of statements; and (5) transforming analysis results into knowledge points. According to the natural language knowledge acquisition method based on the semantic matching driving, an analysis scheme better accordant with semantic logics can be selected as the final analysis result from multiple grammatical analysis schemes according to semantic matching values by adopting semantic matching information to cooperate with common syntax rules in a small quantity of natural languages. Through the adoption of the method, the natural language statement analysis can be carried out and knowledge contained in the statements of the natural languages can be acquired. Experiments indicate that the method has higher feasibility.

Description

technical field [0001] The invention belongs to the field of computer natural language understanding, in particular to a method for acquiring natural language knowledge driven by semantic matching. Background technique [0002] In knowledge integration, a large amount of knowledge is contained in natural language sentences. Only when the automatic analysis of natural language sentences is realized, can the knowledge contained in sentences be effectively obtained. Therefore, natural language processing technology has become the key basic technology of knowledge integration. [0003] Natural language processing technology mainly includes rule-based methods and statistical-based methods, but both methods do not make full use of semantic information, and it is difficult to obtain high-quality processing results. Therefore, researchers pay more and more attention to the role of semantics, and there are methods to analyze natural language based on wordnet, hownet, framenet and ot...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/28G06F17/27
Inventor 刘运通郭磊王爱民
Owner ANYANG NORMAL UNIV
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