Construction method of domain dictionary

Abstract

The invention relates to the field of natural language processing, and in particular relates to a construction method of a domain dictionary. The method comprises the following steps: on the basis of automatic acquisition of a text keyword, clustering to-be-processed texts to form different topic text sets; selecting a part of seed words in a domain text set of a to-be-constructed dictionary through manual examination; on the basis, analyzing the distance of the clustered topic text sets and the selected domain seed words in relationship, and only retaining the top text sets which are relatively close in relationship for expanding the domain dictionary; and in a related domain, performing automatic expansion of the domain dictionary by combining an algorithm in the related domain to obtain a corresponding dictionary. According to the method provided by the invention, the to-be-constructed domain dictionary can be automatically expanded through a few of part of seed words on the basis of automatic differentiation of the domains of the text topics; the construction efficiency of the dictionary is relatively high, the accuracy is high, and the pertinence of the domain is strong; the method has wide application prospect in text analysis and natural language processing field.

Description

technical field [0001] The invention relates to the field of natural language processing, in particular to a method for constructing a field dictionary. Background technique [0002] With the rapid development of the Internet, a large amount of public web data has been generated, which has also spurred various emerging industries based on big data technology, such as Internet medical care, Internet education, corporate or personal credit investigation, etc. The rise and prosperity of these Internet industries are inseparable from the analysis of a large amount of data information. Natural language processing plays an important role in big data analysis. In the face of massive network text resources, natural language processing analysis methods can be used to automatically and intelligently judge the emotional tendency contained in the text or the text publisher, whether it is in public opinion It has vital practical application significance in both analysis and business inv...

AI Technical Summary

Problems solved by technology

[0004] The sentiment analysis method based on the sentiment dictionary is targeted analysis and excavation. The dictionaries adopted in different fields are also very different. At present, the existing field dictionaries lack the applicability to specific problems and are not very targeted.

When analyzing specific fields or specific topics, using existing large and broad domain dictionaries cannot achieve good analysis results. It is necessary to build targeted domain dictionaries, but manually constructing dictionaries is very time-consuming and labor-intensive; Can not meet the needs of massive text analysis

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