Knowledge Discovery in Text Mining Technique Using Association Rules Extraction

Abstract

This paper describes text mining technique for automatically extracting association rules from collections of textual documents. The technique called, Extracting Association Rules from Text (EART). It depends on keyword features for discover association rules amongst keywords labeling the documents. EART system ignores the order in which the words occur, but instead focusing on the words and their statistical distributions in documents. The system based on Information Retrieval scheme (TF-IDF) for selecting most important keywords for association rules generation. It consists of three phases: Text Preprocessing phase (transformation, filtration, stemming and indexing of the documents), Association Rule Mining (ARM) phase (applying our designed algorithm for Generating Association Rules based on Weighting scheme GARW) and Visualization phase (visualization of results). Experiments applied on Online WebPages related to the cryptography. The extracted association rules contain important features.