Data Mining technique and its Application: Association rules mining for Korean language

Abstract

This paper explains the importance of Association Rules Mining for of Korean language (text). Association rules mining can also be used for mining association rules from textual data with some modifications. Which can then, help for generating statistical thesaurus, to mine grammatical rules and to search large data efficiently. Although various association rules mining techniques have successfully used for market basket analysis but very few has applied on Korean text. A proposed Korean language mining model calculates and extracts meaningful patterns (association rules) between words and presents the hidden knowledge. First it cleans and integrates data and select relevant data then transform into transactional database. Then data mining techniques are used on data source to extract hidden patterns. These patterns are evaluated by specific rules until we get the valid and satisfactory result. We have tested on Korean news corpus and results have shown that it has worked well, and the results were adequate enough to research further.