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Semantic similarity assessment of words using weighted WordNet

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Abstract

Word and concept similarity assessment is one of the most important elements in natural language processing and information and knowledge retrieval. WordNet, as a popular concept hierarchy, is used in many such applications. Similarity of words in WordNet is also considered in recent researches. Many researches that use WordNet, have calculated similarity between each pair-word by considering depth of subsumer of the words and shortest path between them. In this paper, three novel models to make better semantic word similarity measure have been presented and it was improved by giving weights to the edges of WordNet hierarchy. It was considered that the nearer an edge is to the root in the hierarchy, the less effect it has in calculating the similarity. Therefore, we have offered a new formula for weighting the edges of hierarchy and based on that, we calculated the distance between two words and depth of words; and then tuned parameters of the transfer functions using particle swarm optimization. Experimental results on a common benchmark, created by human judgment, show that the resultant correlation improved; furthermore our formulae were applied to a more realistic application called sentence similarity assessment and it led to the better results.

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Acknowledgments

This research is partially supported by research chancellor, Ferdowsi University of Mashhad, Mashhad, Iran under the contract no. 13203.

We would like to thank F. Pourgholamali for helping us to evaluate our similarity formulae in the sentence similarity application.

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Authors and Affiliations

  1. Communications and Computer Research Center, Ferdowsi University of Mashhad, Mashhad, Iran

    Mostafa Ghazizadeh Ahsaee

  2. Department of Computer Engineering, Ferdowsi University of Mashhad, Mashhad, Iran

    Mostafa Ghazizadeh Ahsaee & Mahmoud Naghibzadeh

  3. Department of Computer Engineering, Torbat-e Heydariyeh Higher Education Complex, Torbat Heydariyeh, Iran

    S. Ehsan Yasrebi Naeini

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  1. Mostafa Ghazizadeh Ahsaee
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  2. Mahmoud Naghibzadeh
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  3. S. Ehsan Yasrebi Naeini
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Correspondence to Mostafa Ghazizadeh Ahsaee.

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Ghazizadeh Ahsaee, M., Naghibzadeh, M. & Yasrebi Naeini, S.E. Semantic similarity assessment of words using weighted WordNet. Int. J. Mach. Learn. & Cyber. 5, 479–490 (2014). https://doi.org/10.1007/s13042-012-0135-3

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  • DOI: https://doi.org/10.1007/s13042-012-0135-3

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