Data Mining and Intelligent Matching Algorithm in Electric Power Terminology Database

Abstract

The paper designs a method and system for automatic extraction of professional vocabulary in the electric power field based on data mining and matching algorithms. The system extracts professional vocabulary related to power marketing from the corpus in the field of power marketing, converts it into corresponding English and adds it to the professional vocabulary of power marketing. Then we will collect the relevant vocabulary of the power system and the corresponding translation and add it to the professional vocabulary of power marketing. The thesis establishes a two-level index structure for the professional vocabulary of electric power marketing. We search the professional vocabulary database of electric power marketing, the order of retrieval is electric power system vocabulary, general dictionary, electric power marketing field extraction vocabulary, and the search result is returned to the user after the retrieval. The experiment verified that the system facilitates the efficient retrieval of user vocabulary, and then realizes the automatic conversion of professional vocabulary in the marketing standardization design results, so as to improve the quality and efficiency of professional vocabulary conversion.