Discovering Synonyms Based on Frequent Termsets

Authors:
Henryk Rybinski;Marzena Kryszkiewicz;Grzegorz Protaziuk;Adam Jakubowski;Alexandre Delteil
Affiliations:
ICS, Warsaw University of Technology,;ICS, Warsaw University of Technology,;ICS, Warsaw University of Technology,;ICS, Warsaw University of Technology,;France Telecome R & D,
Venue:
RSEISP '07 Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms
Year:
2007

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Abstract

Synonymy has been of high importance in information retrieval and automatic indexing. Recently, in the view of special needs for domain ontology building and maintenance, the problem returns with a higher demand. In the presented paper, we present a novel text mining approach to discovering synonyms or close meaning terms. The offered measures of closeness of terms (or their contexts) are expressed by means of data mining notions; namely, frequent termsets and association rules. The measures can be calculated by using data mining techniques, such as the well known Apriori algorithm. The approach is domain-independent and large-scale. It is, however, restricted to the recognition of parts of speech. In that sense the approach is language dependent, up to the language dependency of the parts of speech tagging process. The experimental results obtained with the approach are presented.