TRUMIT: A Tool to Support Large-Scale Mining of Text Association Rules

  • Robert Neumayer
  • George Tsatsaronis
  • Kjetil Nørvåg
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6913)


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.


  1. 1.
    Agrawal, R., Imieliński, T., Swami, A.: Mining association rules between sets of items in large databases. SIGMOD Record 22, 207–216 (1993)CrossRefGoogle Scholar
  2. 2.
    Amir, A., Aumann, Y., Feldman, R., Fresko, M.: Maximal association rules: A tool for mining associations in text. Journal of Int. Inf. Systems 25(3), 333–345 (2005)Google Scholar
  3. 3.
    Kurashima, T., Fujimura, K., Okuda, H.: Discovering association rules on experiences from large-scale blog entries. In: Boughanem, M., Berrut, C., Mothe, J., Soule-Dupuy, C. (eds.) ECIR 2009. LNCS, vol. 5478, pp. 546–553. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  4. 4.
    Nørvåg, K., Fivelstad, O.K.: Semantic-based temporal text-rule mining. In: Gelbukh, A. (ed.) CICLing 2009. LNCS, vol. 5449, pp. 442–455. Springer, Heidelberg (2009)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Robert Neumayer
    • 1
  • George Tsatsaronis
    • 2
  • Kjetil Nørvåg
    • 1
  1. 1.Department of Computer and Information ScienceNorwegian University of Science and TechnologyTrondheimNorway
  2. 2.Biotechnology CenterTechnical University of DresdenGermany

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