TRUMIT: a tool to support large-scale mining of text association rules

Authors:
Robert Neumayer;George Tsatsaronis;Kjetil Nørvåg
Affiliations:
Norwegian University of Science and Technology, Department of Computer and Information Science, Trondheim, Norway;Biotechnology Center, Technical University of Dresden, Germany;Norwegian University of Science and Technology, Department of Computer and Information Science, Trondheim, Norway
Venue:
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part III
Year:
2011

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Abstract

Due to the nature of textual data the application of association rule mining in text corpora has attracted the focus of the research scientific community for years. In this paper we demonstrate a system that can efficiently mine association rules from text. The system annotates terms using several annotators, and extracts text association rules between terms or categories of terms. An additional contribution of this work is the inclusion of novel unsupervised evaluation measures for weighting and ranking the importance of the text rules. We demonstrate the functionalities of our system with two text collections, a set ofWikileaks documents, and one from TREC-7.