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A Study of the Effect of Document Representations in Clustering-Based Cross-Document Coreference Resolution

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Multi-source, Multilingual Information Extraction and Summarization

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Abstract

Finding information about people on huge text collections or on-line repositories on the Web is a common activity. We describe experiments aiming at identifying the contribution of semantic information (e.g., named entities) and summarization (e.g., sentence extracts) in a cross-document coreference resolution system. Our system uses a clustering-based algorithm to group documents referring to the same entity. Clustering uses vector representations created by summarization and semantic tagging components. We investigate different clustering configurations and show that selection of the type of summary and the type of term to be used for vector representation is important to achieve good performance.

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Acknowledgements

We thank the reviewers for their comments and suggestions which helped improve the final version of this paper. Horacio Saggion is grateful to a fellowship from Programa Ramón y Cajal, Ministerio de Ciencia e Innovación, Spain. We acknowledge the support from the editors of this volume.

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Authors and Affiliations

  1. Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain

    Horacio Saggion

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  1. Horacio Saggion
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Correspondence to Horacio Saggion .

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Editors and Affiliations

  1. Universite Sorbonne Nouvelle, LATTICE-CNRS, Ecole Normale Superieure and, rue d'Ulm 45, Paris, 75005, France

    Thierry Poibeau

  2. , Information & Communication Technologies, Universitat Pompeu Fabra, C/ Tanger 122-140, Barcelona, 08018, Spain

    Horacio Saggion

  3. Institute for Computer Science, Polish Acadmey of Science, ul. Jana Kazimierza 5, Warsaw, 01-248, Poland

    Jakub Piskorski

  4. Department of Computer Science, University of Helsinki, Gustaf Hällströmin katu 2, Helsinki, 00014, Finland

    Roman Yangarber

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Saggion, H. (2013). A Study of the Effect of Document Representations in Clustering-Based Cross-Document Coreference Resolution. In: Poibeau, T., Saggion, H., Piskorski, J., Yangarber, R. (eds) Multi-source, Multilingual Information Extraction and Summarization. Theory and Applications of Natural Language Processing. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28569-1_6

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  • DOI: https://doi.org/10.1007/978-3-642-28569-1_6

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