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Association Rule Mining Based on the Semantic Categories of Tourism Information

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Advances in Neural Networks - ISNN 2008 (ISNN 2008)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5264))

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Abstract

It is difficult for traditional data mining algorithms to mine semantic information from text set because of its complexity and high dimension. To solve this problem, the semantic categories of words appearing in tourism emergency reports are studied, and a semantic association rule mining algorithm is presented based on these categories. Association words are also gained from these rules, which can better describe the semantic contents of the texts. Quantum-inspired genetic algorithm is utilized to improve the effectiveness of rule-searching process. Experiments show the better results than traditional methods.

This work is supported by National Natural Science Foundation of China (No. 60773112) and Beijing Natural Science Foundation (No.4082021, No.4072018).

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References

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Author information

Authors and Affiliations

  1. Information Engineering School, University of Science and Technology Beijing, Beijing, 100083, China

    Yipeng Zhou, Guangping Zeng & Xuyan Tu

  2. School of Computer Science, Beijing Technology and Business University, Beijing, 100037, China

    Yipeng Zhou

  3. Beijing Key Lab of Intelligent Telecommunication Software and Multimedia, School of Computer Science and Technology, Beijing University of Posts and Telecommunications, Beijing, 100876, China

    Junping Du

Authors
  1. Yipeng Zhou
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  2. Junping Du
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  3. Guangping Zeng
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  4. Xuyan Tu
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Technology, Tsinghu University, 100084, Beijing, China

    Fuchun Sun

  2. Institute TAMS (Technical Aspects of Multimodal Systems), department of Informatics, University of Hamburg, Vogt-Koelln-Straße 30, 22527, Hamburg, Germany

    Jianwei Zhang

  3. Intel China Research Center, 8/F, Peking University, Department of Machine Intelligence, 100871, Beijing, China

    Ying Tan

  4. Department of Mathematics, Southeast University, 210096, Nanjing, China

    Jinde Cao

  5. Departamento de Control Automático, CINVESTAV-IPN, A.P. 14-740, Av.IPN 2508, 07360, México D.F., México

    Wen Yu

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© 2008 Springer-Verlag Berlin Heidelberg

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Zhou, Y., Du, J., Zeng, G., Tu, X. (2008). Association Rule Mining Based on the Semantic Categories of Tourism Information. In: Sun, F., Zhang, J., Tan, Y., Cao, J., Yu, W. (eds) Advances in Neural Networks - ISNN 2008. ISNN 2008. Lecture Notes in Computer Science, vol 5264. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87734-9_8

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  • DOI: https://doi.org/10.1007/978-3-540-87734-9_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-87733-2

  • Online ISBN: 978-3-540-87734-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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