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Ontology-Based Hazard Information Extraction from Chinese Food Complaint Documents

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Advances in Swarm Intelligence (ICSI 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7332))

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Abstract

Ensuring food safety has become a global research subject these years. In this paper, a knowledge model of domain ontology with the aim of hazard information extraction from Chinese food complaint documents has been designed based on ontology theory. Two components are essential to this model the learning model and the extraction model. In the learning model, we propose the algorithms of seed words selection and related words generation. In the extraction model we propose the algorithms of hazard information extraction and modifying related words. We compare the results of our method with the method of traditional ontology based information extraction and traditional information extraction. The results show that the method we proposed has better indexes.

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Author information

Authors and Affiliations

  1. School of Computer Science and Information Technology, Northeast Normal University, Changchun, Jilin, China, 130117

    Xiquan Yang, Rui Gao, Zhengfu Han & Xin Sui

Authors
  1. Xiquan Yang
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  2. Rui Gao
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  3. Zhengfu Han
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  4. Xin Sui
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Editor information

Editors and Affiliations

  1. Key Laboratory of Machine Perception (MOE), Peking University, Department of Machine Intelligence, School of Electronics Engineering and Computer Science, Peking University, 100871, Beijing, China

    Ying Tan

  2. Department of Electrical and Electronic Engineering, Xi’an Jiaotong-Liverpool University, Suzhou, China

    Yuhui Shi

  3. Shenzhen City Key Laboratory of Embedded System Design, College of Computer Science and Software Engineering, Shenzhen University, 518060, Shenzhen, China

    Zhen Ji

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© 2012 Springer-Verlag Berlin Heidelberg

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Yang, X., Gao, R., Han, Z., Sui, X. (2012). Ontology-Based Hazard Information Extraction from Chinese Food Complaint Documents. In: Tan, Y., Shi, Y., Ji, Z. (eds) Advances in Swarm Intelligence. ICSI 2012. Lecture Notes in Computer Science, vol 7332. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31020-1_19

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  • DOI: https://doi.org/10.1007/978-3-642-31020-1_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31019-5

  • Online ISBN: 978-3-642-31020-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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