Mining concept associations for knowledge discovery in large textual databases

In this paper, we describe a new approach for mining concept associations from large text collections. The concepts are short sequences of words that occur frequently together across the text collections. It is these concepts that convey most of the meaning in any language. Our goal is to extract interesting associations among concepts that co-occur within the text collections. Interesting association between the concepts is mined using association rule mining algorithm. Finally we construct directed graph from current rules. The experimental result shows that our approach can efficiently find interesting concept associations in large text collections. Categories and Subject Descriptors H.2.8 [Database Applications] - Data Mining, H.2.4 [Systems] – textual databases, I.2.7 [Natural Language Processing] Text analysis, and H.3.6 [Library Automation] - Large text archives General Terms Algorithms, Management, Measurement, Performance. Keywords Text Data Mining, Association Rule Mining,...

• Type: Conference
• Year: 2005
• Where: SAC
• Authors: Xiaowei Xu, Mutlu Mete, Nurcan Yuruk
• Keywords: Applied Computing, Concept Associations, Large Text Collections, SAC 2005, Text Collections