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Authors: Thi Thuy Anh Nguyen and Stefan Conrad

Affiliation: Heinrich-Heine-University Düsseldorf, Germany

Keyword(s): Information-theoretic Model, Feature-based Measure, String-based Measure, Similarity.

Abstract: Measurement of similarity plays an important role in data mining and information retrieval. Several techniques for calculating the similarities between objects have been proposed so far, for example, lexical-based, structure-based and instance-based measures. Existing lexical similarity measures usually base on either ngrams or Dice’s approaches to obtain correspondences between strings. Although these measures are efficient, they are inadequate in situations where strings are quite similar or the sets of characters are the same but their positions are different in strings. In this paper, a lexical similarity approach combining information-theoretic model and edit distance to determine correspondences among the concept labels is developed. Precision, Recall and F-measure as well as partial OAEI benchmark 2008 tests are used to evaluate the proposed method. The results show that our approach is flexible and has some prominent features compared to other lexical-based methods.

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Paper citation in several formats:
Nguyen, T. and Conrad, S. (2014). Applying Information-theoretic and Edit Distance Approaches to Flexibly Measure Lexical Similarity. In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (IC3K 2014) - SSTM; ISBN 978-989-758-048-2; ISSN 2184-3228, SciTePress, pages 505-511. DOI: 10.5220/0005170005050511

@conference{sstm14,
author={Thi Thuy Anh Nguyen. and Stefan Conrad.},
title={Applying Information-theoretic and Edit Distance Approaches to Flexibly Measure Lexical Similarity},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (IC3K 2014) - SSTM},
year={2014},
pages={505-511},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005170005050511},
isbn={978-989-758-048-2},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (IC3K 2014) - SSTM
TI - Applying Information-theoretic and Edit Distance Approaches to Flexibly Measure Lexical Similarity
SN - 978-989-758-048-2
IS - 2184-3228
AU - Nguyen, T.
AU - Conrad, S.
PY - 2014
SP - 505
EP - 511
DO - 10.5220/0005170005050511
PB - SciTePress

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