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

Robert Neumayer; George Tsatsaronis; Kjetil Nørvåg

doi:10.1007/978-3-642-23808-6_48

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

Robert Neumayer
, George Tsatsaronis
, Kjetil Nørvåg

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

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 of Wikileaks documents, and one from TREC-7.

Original language	English
Title of host publication	Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2011, Proceedings
Publisher	Springer Verlag
Pages	646-649
Number of pages	4
Edition	PART 3
ISBN (Print)	9783642238079
DOIs	https://doi.org/10.1007/978-3-642-23808-6_48
State	Published - 2011
Externally published	Yes

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 3
Volume	6913 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

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10.1007/978-3-642-23808-6_48

Cite this

Neumayer, R., Tsatsaronis, G., & Nørvåg, K. (2011). TRUMIT: A tool to support large-scale mining of text association rules. In Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2011, Proceedings (PART 3 ed., pp. 646-649). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6913 LNAI, No. PART 3). Springer Verlag. https://doi.org/10.1007/978-3-642-23808-6_48

Neumayer, Robert ; Tsatsaronis, George ; Nørvåg, Kjetil. / TRUMIT : A tool to support large-scale mining of text association rules. Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2011, Proceedings. PART 3. ed. Springer Verlag, 2011. pp. 646-649 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 3).

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Neumayer, R, Tsatsaronis, G & Nørvåg, K 2011, TRUMIT: A tool to support large-scale mining of text association rules. in Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2011, Proceedings. PART 3 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 3, vol. 6913 LNAI, Springer Verlag, pp. 646-649. https://doi.org/10.1007/978-3-642-23808-6_48

TRUMIT: A tool to support large-scale mining of text association rules. / Neumayer, Robert; Tsatsaronis, George; Nørvåg, Kjetil.
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2011, Proceedings. PART 3. ed. Springer Verlag, 2011. p. 646-649 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6913 LNAI, No. PART 3).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - 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 of Wikileaks documents, and one from TREC-7.

AB - 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 of Wikileaks documents, and one from TREC-7.

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DO - 10.1007/978-3-642-23808-6_48

M3 - Contribución a la conferencia

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Neumayer R, Tsatsaronis G, Nørvåg K. TRUMIT: A tool to support large-scale mining of text association rules. In Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2011, Proceedings. PART 3 ed. Springer Verlag. 2011. p. 646-649. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 3). doi: 10.1007/978-3-642-23808-6_48

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

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