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Discovering the Primary Factors of Cancer from Health and Living Habit Questionnaires

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Discovery Science (DS 1999)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1721))

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3 Conclusions

We have successfully obtained mining results with the questionnaire data. This application is very significant because the results are directly apply to the cancer prevention and cancer control. The following step is to collect more data (the other district questionnaire data) and do further mining to generate more genaral rules.

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References

  1. P. Cabena et al. Discovering data mining. Prentice Hall PTR, 1998.

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  2. IBM Intelligent Miner for Data. Using the Intelligent Miner for Data. IBM Corp., Third Edition, 1998.

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  3. M. Mehta, R. Agrawal, and J. Rissanen. SLIQ: A fast scalable classifier for data mining. In Proc. of the Fifth Int’l Conference on Extending Database Technology, Avignon, France, 1996. Morgan Kaufmann.

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Author information

Authors and Affiliations

  1. Business Intelligent Solutions, IBM Japan, Tokyo, 103-8510, Japan

    Xiaolong Zhang & Tetsuo Narita

Authors
  1. Xiaolong Zhang
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  2. Tetsuo Narita
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Editor information

Editors and Affiliations

  1. Department of Informatics, Kyushu University, 6-10-1 Hakozaki, Higashi-ku, Fukuoka, 812-8581, Japan

    Setsuo Arikawa

  2. Graduate School of Media and Governance, Keio University, 5322 Endoh, Fujisawa-shi, Kanagawa, 252-8520, Japan

    Koichi Furukawa

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© 1999 Springer-Verlag Berlin Heidelberg

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Zhang, X., Narita, T. (1999). Discovering the Primary Factors of Cancer from Health and Living Habit Questionnaires. In: Arikawa, S., Furukawa, K. (eds) Discovery Science. DS 1999. Lecture Notes in Computer Science(), vol 1721. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46846-3_53

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  • DOI: https://doi.org/10.1007/3-540-46846-3_53

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66713-1

  • Online ISBN: 978-3-540-46846-2

  • eBook Packages: Springer Book Archive

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