Title :
Knowledge Discovery in Text Mining Technique Using Association Rules Extraction
Author :
Bhujade, Vaishali ; Janwe, N.J.
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.
Keywords :
cryptography; data mining; data visualisation; information retrieval; statistical distributions; text analysis; Online WebPages; association rule mining phase; association rules extraction; cryptography; information retrieval scheme; knowledge discovery; statistical distribution; text mining; text preprocessing phase; visualization phase; Communication systems; Computational intelligence; Association Rules; Data Mining; Knowledge Discovery; Text Mining;
Conference_Titel :
Computational Intelligence and Communication Networks (CICN), 2011 International Conference on
Conference_Location :
Gwalior
Print_ISBN :
978-1-4577-2033-8
DOI :
10.1109/CICN.2011.104