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Conversation Intention Perception Based on Knowledge Base

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Trends and Applications in Knowledge Discovery and Data Mining (PAKDD 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8643))

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Abstract

Web Intelligence is gaining its growth in a rapid speed. The notion of wisdom, which is considered as the next paradigm shift of WI, has become a hot research topic in recent years. The basic application of wisdom is making a short conversation in an interactive and understandable way based on the huge web resources. However, current conversation system normally applies the recognition of semantic similarities in the prepared database, neglecting the true intention hiding in the expression. In this paper, we present a model based on the medical Q&A knowledge base to overcome this challenge. The knowledge base includes three parts: disease entity, medicine, properties. A simple graph path algorithm based on words direction and relation weight adjustment is used to realize conversation intention perception. The experimental results show that this method can effectively perceive types of intention. This method can also be applied in deep understanding of other intelligent systems such as classifications and text mining.

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Notes

  1. 1.

    http://www.wikipedia.org/

  2. 2.

    http://wordnet.princeton.edu/

  3. 3.

    http://www.baike.com/

  4. 4.

    http://kb.mozillazine.org/Knowledge_Base

  5. 5.

    http://www.geonames.org/

  6. 6.

    http://www.120ask.com

  7. 7.

    http://baike.baidu.com/

  8. 8.

    https://pypi.python.org/pypi/jieba/

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Author information

Authors and Affiliations

  1. Shanghai Key Laboratory of Scalable Computing and Systems, Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China

    Yi-Zheng Chen, Hua-Kang Li & Yi Liu

Authors
  1. Yi-Zheng Chen
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  2. Hua-Kang Li
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  3. Yi Liu
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Corresponding author

Correspondence to Yi-Zheng Chen .

Editor information

Editors and Affiliations

  1. National Chiao Tung University, Hsinchu, Taiwan

    Wen-Chih Peng

  2. Google Research, Mountain View, California, USA

    Haixun Wang

  3. University of Melbourne, Melbourne, Victoria, Australia

    James Bailey

  4. National Cheng Kung University, Tainan, Taiwan

    Vincent S. Tseng

  5. Japan Advanced Institute of Science and Technology, Nomi City, Japan

    Tu Bao Ho

  6. Nanjing University, Nanjing, China

    Zhi-Hua Zhou

  7. National Chengchi University, Taipei, Taiwan

    Arbee L.P. Chen

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© 2014 Springer International Publishing Switzerland

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Chen, YZ., Li, HK., Liu, Y. (2014). Conversation Intention Perception Based on Knowledge Base. In: Peng, WC., et al. Trends and Applications in Knowledge Discovery and Data Mining. PAKDD 2014. Lecture Notes in Computer Science(), vol 8643. Springer, Cham. https://doi.org/10.1007/978-3-319-13186-3_1

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  • DOI: https://doi.org/10.1007/978-3-319-13186-3_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-13185-6

  • Online ISBN: 978-3-319-13186-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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