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International Conference on Context-Aware Systems and Applications

ICCASA 2013: Context-Aware Systems and Applications pp 369–378Cite as

Combining Heuristics and Learning for Entity Linking

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Abstract

Entity linking refers to the task of mapping name strings in a text to their corresponding entities in a given knowledge base. It is an essential component in natural language processing applications and a challenging task. This paper proposes a method that combines heuristics and learning for entity linking by (i) learning coherence among co-occurrence entities within the text based on Wikipedia’s link structure and (ii) exploiting some heuristics based on the contexts and coreference relations among name strings. The experiment results on TAC-KBP2011 dataset show that our method achieves performance comparable to the state-of-the-art methods. The results also show that the proposed model is simple because of using a classifier trained on just two popular features in combination with some heuristics, but effective.

The original version of this chapter was revised: The copyright line was incorrect. This has been corrected. The Erratum to this chapter is available at DOI: 10.1007/978-3-319-05939-6_37

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Author information

Authors and Affiliations

  1. Ton Duc Thang University, Ho Chi Minh, Vietnam

    Hien T. Nguyen

Authors
  1. Hien T. Nguyen
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Correspondence to Hien T. Nguyen .

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Editors and Affiliations

  1. Faculty of Information Technology, Nguyen Tat Thanh University, Vietnam, Ho Chi Minh City, Vietnam

    Phan Cong Vinh

  2. Concordia University, Montreal, Canada

    Vangalur Alagar

  3. University of Limerick, Limerick, Ireland

    Emil Vassev

  4. University of Allahabad, Allahabad, India

    Ashish Khare

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© 2014 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering

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Nguyen, H.T. (2014). Combining Heuristics and Learning for Entity Linking. In: Vinh, P., Alagar, V., Vassev, E., Khare, A. (eds) Context-Aware Systems and Applications. ICCASA 2013. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 128. Springer, Cham. https://doi.org/10.1007/978-3-319-05939-6_36

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  • DOI: https://doi.org/10.1007/978-3-319-05939-6_36

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-05938-9

  • Online ISBN: 978-3-319-05939-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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