Alternative Interest Measures for Mining Associations in Databases
IEEE Transactions on Knowledge and Data Engineering
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
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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.