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International Workshop on Worldwide Language Service Infrastructure

WLSI 2015: Worldwide Language Service Infrastructure pp 188–199Cite as

Effectiveness of Keyword and Semantic Relation Extraction for Knowledge Map Generation

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9442))

Abstract

We explore the named entity (NE) recognition and semantic relation extraction technique on the Thai cultural database. Within the limited domain and well-structured database, our proposed method can perform in an acceptable high accuracy to generate the tuples of semantic relation for expressing the essence of the record in terms of infobox and knowledge map. In this paper, we propose a semantic relation extraction approach based on simple relation templates that determine relation types and their arguments. We attempt to reduce semantic drift of the arguments by using named entity models as semantic constraints. Experimental results indicate that our approach is very promising. We successfully apply our approach to a cultural database and discover more than 18,000 relation instances with expected high accuracy.

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Notes

  1. 1.

    http://www.m-culture.in.th/.

  2. 2.

    http://dublincore.org/documents/2012/06/14/dces/.

  3. 3.

    http://lucene.apache.org/solr/.

  4. 4.

    http://www.cnts.ua.ac.be/conll2000/chunking/conlleval.txt.

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Acknowledgement

The experiments in this paper are conducted on the Thai Cultural Database of the Ministry of Culture, developed under the central information project since November 2010.

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Authors and Affiliations

  1. Sirindhorn International Institute of Technology, Thammasat University, Bangkok, Thailand

    Virach Sornlertlamvanich

  2. Graduate School of Information Sciences, Tohoku University, Sendai, Japan

    Canasai Kruengkrai

Authors
  1. Virach Sornlertlamvanich
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  2. Canasai Kruengkrai
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Corresponding author

Correspondence to Virach Sornlertlamvanich .

Editor information

Editors and Affiliations

  1. Unit of Design, Kyoto University, Kyoto, Japan

    Yohei Murakami

  2. Kyoto University, Kyoto, Japan

    Donghui Lin

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Sornlertlamvanich, V., Kruengkrai, C. (2016). Effectiveness of Keyword and Semantic Relation Extraction for Knowledge Map Generation. In: Murakami, Y., Lin, D. (eds) Worldwide Language Service Infrastructure. WLSI 2015. Lecture Notes in Computer Science(), vol 9442. Springer, Cham. https://doi.org/10.1007/978-3-319-31468-6_14

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  • DOI: https://doi.org/10.1007/978-3-319-31468-6_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-31467-9

  • Online ISBN: 978-3-319-31468-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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