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Review of Relation Extraction Methods: What Is New Out There?

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Analysis of Images, Social Networks and Texts (AIST 2014)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 436))

Abstract

Relation extraction is a part of Information Extraction and an established task in Natural Language Processing. This paper presents an overview of the main directions of research and recent advances in the field. It reviews various techniques used for relation extraction including knowledge-based, supervised and self-supervised methods. We also mention applications of relation extraction and identify current trends in the way the field is developing.

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Notes

  1. 1.

    http://www.itl.nist.gov/iaui/894.02/related_projects/muc/

  2. 2.

    http://www.itl.nist.gov/iad/894.01/tests/ace/

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  1. University of Wolverhampton, Wolverhampton, UK

    Natalia Konstantinova

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  1. Natalia Konstantinova
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Correspondence to Natalia Konstantinova .

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  1. National Research University Higher School of Economics, Moscow, Russia

    Dmitry I. Ignatov

  2. Krasovsky Inst. of Math. and Mechanics, Yekaterinburg, Russia

    Mikhail Yu. Khachay

  3. Université catholique de Louvain, Moscow, Russia

    Alexander Panchenko

  4. University of Wolverhampton, Wolverhampton, United Kingdom

    Natalia Konstantinova

  5. National Research University, Moscow, Russia

    Rostislav E. Yavorsky

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Konstantinova, N. (2014). Review of Relation Extraction Methods: What Is New Out There?. In: Ignatov, D., Khachay, M., Panchenko, A., Konstantinova, N., Yavorsky, R. (eds) Analysis of Images, Social Networks and Texts. AIST 2014. Communications in Computer and Information Science, vol 436. Springer, Cham. https://doi.org/10.1007/978-3-319-12580-0_2

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