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Design, Implementation and Evaluation of a New Semantic Similarity Metric Combining Features and Intrinsic Information Content

  • Conference paper
On the Move to Meaningful Internet Systems: OTM 2008 (OTM 2008)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5332))

Abstract

In many research fields such as Psychology, Linguistics, Cognitive Science, Biomedicine, and Artificial Intelligence, computing semantic similarity between words is an important issue. In this paper we present a new semantic similarity metric that exploits some notions of the early work done using a feature based theory of similarity, and translates it into the information theoretic domain which leverages the notion of Information Content (IC). In particular, the proposed metric exploits the notion of intrinsic IC which quantifies IC values by scrutinizing how concepts are arranged in an ontological structure. In order to evaluate this metric, we conducted an on line experiment asking the community of researchers to rank a list of 65 word pairs. The experiment’s web setup allowed to collect 101 similarity ratings, and to differentiate native and non-native English speakers. Such a large and diverse dataset enables to confidently evaluate similarity metrics by correlating them with human assessments. Experimental evaluations using WordNet indicate that our metric, coupled with the notion of intrinsic IC, yields results above the state of the art. Moreover, the intrinsic IC formulation also improves the accuracy of other IC based metrics. We implemented our metric and several others in the Java WordNet Similarity Library.

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Author information

Authors and Affiliations

  1. D.E.I.S, University of Calabria, Italy

    Giuseppe Pirró

  2. DEI-CISUC, University of Coimbra, Portugal

    Nuno Seco

Authors
  1. Giuseppe Pirró
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  2. Nuno Seco
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Editor information

Editors and Affiliations

  1. STARLab, Vrije Universiteit Brussel (VUB),, Bldg G/10, Pleinlaan 2, 1050, Brussels, Belgium

    Robert Meersman

  2. School of Computer Science and Information Technology, RMIT University, Bld 10.10, 376-392 Swanston Street, VIC 3001, Melbourne,, Australia

    Zahir Tari

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© 2008 Springer-Verlag Berlin Heidelberg

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Pirró, G., Seco, N. (2008). Design, Implementation and Evaluation of a New Semantic Similarity Metric Combining Features and Intrinsic Information Content. In: Meersman, R., Tari, Z. (eds) On the Move to Meaningful Internet Systems: OTM 2008. OTM 2008. Lecture Notes in Computer Science, vol 5332. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88873-4_25

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  • DOI: https://doi.org/10.1007/978-3-540-88873-4_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-88872-7

  • Online ISBN: 978-3-540-88873-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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