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Cross-Language High Similarity Search Using a Conceptual Thesaurus

  • Parth Gupta
  • Alberto Barrón-Cedeño
  • Paolo Rosso
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7488)

Abstract

This work addresses the issue of cross-language high similarity and near-duplicates search, where, for the given document, a highly similar one is to be identified from a large cross-language collection of documents. We propose a concept-based similarity model for the problem which is very light in computation and memory. We evaluate the model on three corpora of different nature and two language pairs English-German and English-Spanish using the Eurovoc conceptual thesaurus. Our model is compared with two state-of-the-art models and we find, though the proposed model is very generic, it produces competitive results and is significantly stable and consistent across the corpora.

Keywords

Machine Translation Language Pair Name Entity Comparable Corpus Plagiarism Detection 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Parth Gupta
    • 1
  • Alberto Barrón-Cedeño
    • 1
  • Paolo Rosso
    • 1
  1. 1.Natural Language Engineering Lab. - ELiRF Department of Information Systems and ComputationUniversitat Politècnica de ValènciaSpain

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