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Computing Semantic Clusters by Semantic Mirroring and Spectral Graph Partitioning

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Abstract

Using the technique of semantic mirroring a graph is obtained that represents words and their translations from a parallel corpus or a bilingual lexicon. The connectedness of the graph holds information about the semantic relations of words that occur in the translations. Spectral graph theory is used to partition the graph, which leads to a grouping of the words in different clusters. We illustrate the method using a small sample of seed words from a lexicon of Swedish and English adjectives and discuss its application to computational lexical semantics and lexicography.

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Authors and Affiliations

  1. Department of Mathematics, Linköping University, Linköping, Sweden

    Lars Eldén & Martin Fagerlund

  2. Department of Computer Science, Linköping University, Linköping, Sweden

    Magnus Merkel & Lars Ahrenberg

Authors
  1. Lars Eldén
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  2. Magnus Merkel
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  3. Lars Ahrenberg
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  4. Martin Fagerlund
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Correspondence to Lars Eldén.

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Eldén, L., Merkel, M., Ahrenberg, L. et al. Computing Semantic Clusters by Semantic Mirroring and Spectral Graph Partitioning. Math.Comput.Sci. 7, 293–313 (2013). https://doi.org/10.1007/s11786-013-0159-4

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  • DOI: https://doi.org/10.1007/s11786-013-0159-4

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