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An Intelligent Web Recommendation System: A Web Usage Mining Approach

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Foundations of Intelligent Systems (ISMIS 2002)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2366))

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Abstract

As an increasing number of Web sites consist of an increasing number of pages, it is more difficult for the users to rapidly reach their own target pages. So the intelligent systems supporting the users in navigation of the Web contents are in high demand. In this paper, we describe an intelligent recommendation system called the system L-R, which constructs user models by mining the Web access logs and recommends the relevant pages to the users based both on the user models and the Web contents. We have evaluated the prototype system and have obtained the positive effects.

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References

  1. H. Kiyomitsu, A. Takeuchi, and K. Tanaka.: Dynamic Web Page Reconfiguration Based on Active Rules, IPSJ Sig Notes, vol. 2000, no. 69 (2000-DBS-122), pp. 383–390, 2000 (in Japanese).

    Google Scholar 

  2. J. Kleinberg: Authoritative sources in a hyperlinked environment. Proc. 9th ACM-SIAM Symposium on Discrete Algorithms, 1998.

    Google Scholar 

  3. T. Mizuhara, T. Nakajima, M. Ohta, and H. Ishikawa: Web Log Data Analysis for Recommendation System, Proc. IPSJ National Convention, 4W-3, 2001 (in Japanese).

    Google Scholar 

  4. B. Mobasher, R. Cooley, and J. Srivastava: Automatic Personalization Based on Web Usage Mining, CACM, vol. 43, no. 8, pp. 142–151, 2000.

    Google Scholar 

  5. T. Nakajima, T. Mizuhara, M. Ohta, and H. Ishikawa: Recommendation System Using User Models based on Web Logs, Proc. IPSJ National Convention, 4W-4, 2001 (in Japanese).

    Google Scholar 

  6. M. Perkowittz and O. Etzioni: Adaptive Web Sites, CACM, vol43, no. 8, pp. 152–158, 2000.

    Google Scholar 

  7. J. Schafer, J. Konstan, and J. Riedl: Recommender Systems in E-Commerce. Proc. ACM Conference on Electronic Commerce (EC-99), pp. 158–166, 1999.

    Google Scholar 

  8. A. Takeuchi, H. Kiyomitsu, and K. Tanaka.: Access Control of Web Content Based on Access Histories, Aggregations and Meta-Rules, IPSJ Sig Notes, vol. 2000, no. 69 (2000-DBS-122), pp. 315–322, 2000 (in Japanese).

    Google Scholar 

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Author information

Authors and Affiliations

  1. Tokyo Metropolitan University, Japan

    Hiroshi Ishikawa, Shohei Yokoyama, Junya Nakayama, Manabu Ohta & Kaoru Katayama

  2. NTT Data Corporatio, USA

    Toshiyuki Nakajima

  3. Hitachi Software Engineering Co., Ltd., Japan

    Tokuyo Mizuhara

Authors
  1. Hiroshi Ishikawa
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  2. Toshiyuki Nakajima
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  3. Tokuyo Mizuhara
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  4. Shohei Yokoyama
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  5. Junya Nakayama
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  6. Manabu Ohta
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  7. Kaoru Katayama
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Editor information

Editors and Affiliations

  1. UFR d’Informatique, Université Claude Bernard Lyon I, 8, boulevard Niels Bohr, 69622, Villeurbanne Cedex, France

    Mohand-Saïd Hacid

  2. Dept. of Computer Science College of IT, University of North Carolina, Charlotte, NC, 28223, USA

    Zbigniew W. Raś

  3. Băt. L. Equipe de Recherche en Ingénierie des Connaissances, Université Lumière Lyon 2, 5, avenue Pierre Mendes-France, 69676, Bron Cedex, France

    Djamel A. Zighed

  4. LRI, Université Paris Sud, Băt. 490, 91405, Orsay Cedex, France

    Yves Kodratoff

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© 2002 Springer-Verlag Berlin Heidelberg

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Cite this paper

Ishikawa, H. et al. (2002). An Intelligent Web Recommendation System: A Web Usage Mining Approach. In: Hacid, MS., Raś, Z.W., Zighed, D.A., Kodratoff, Y. (eds) Foundations of Intelligent Systems. ISMIS 2002. Lecture Notes in Computer Science(), vol 2366. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48050-1_38

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  • DOI: https://doi.org/10.1007/3-540-48050-1_38

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43785-7

  • Online ISBN: 978-3-540-48050-1

  • eBook Packages: Springer Book Archive

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