Named Entity Disambiguation Based on Explicit Semantics

  • Martin Jačala
  • Jozef Tvarožek
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7147)


In our work we present an approach to the Named Entity Disambiguation based on semantic similarity measure. We employ existing explicit semantics present in datasets such as Wikipedia to construct a disambiguation dictionary and vector–based word model. The analysed documents are transformed into semantic vectors using explicit semantic analysis. The relatedness is computed as cosine similarity between the vectors. The experimental evaluation shows that the proposed approach outperforms traditional approaches such as latent semantic analysis.


Surface Form Latent Semantic Analysis Semantic Space Computational Linguistics Semantic Similarity Measure 
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

  • Martin Jačala
    • 1
  • Jozef Tvarožek
    • 1
  1. 1.Institute of Informatics and Software Engineering Faculty of Informatics and Information TechnologiesSlovak University of TechnologyBratislavaSlovakia

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