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Personalized Web Retrieval: Three Agents for Retrieving Web Information

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1599))

Abstract

As information available over the Web grows, so does the need for more effective retrieval tools. In this paper we describe three information retrieval agents currently being developed at the National Taiwan University. While each agent serves a different purpose, they share the common feature of incorporating the need of the users. In other words, all three agents offer personalized services. The first agent is an IR agent that utilizes categorical information to assist a user find relevant Web pages. The second one is a website browsing agent which provides various services in an integrated interface to help a user navigate through a content-rich website. The third is designed to help users find on-line papers in computer science.

This research is partly supported by grant NSC 87-2213-E-002-012 of the National Science Council of the Republic of China.

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References

  1. Rob Barrett, Paul P. Maglio and Daniel C. Kellem, How to Personalize the Web, ACM SIGCHI’97, 1997. Available through http://www.acm.org/sigchi/chi97/proceedings/paper/rcb-wbi.htm (January 28, 1999).

  2. Abraham Bookstein, Explanation and Generalization of Vector Models in Information Retrieval, ACM SIGIR’82, pp. 118–132, 1982.

    Google Scholar 

  3. Chris Buckley and Gerard Salton, Optimization of Relevance Feedback Weights, ACM SIGIR’95, pp. 351–357, 1995.

    Google Scholar 

  4. Fah-Chun Cheong, Internet Agents: Spiders, Wanderers, Brokers, and Bots, New Riders Publishing, Indianapolis, Indiana, 1996.

    Google Scholar 

  5. Donna Harman, Relevance Feedback Revisited, ACM SIGIR’92, pp. 1–10, 1992.

    Google Scholar 

  6. Min-Hung Lee, Java-based Personal Proxy Server and its Applications, Master Thesis, National Taiwan University, 1997.

    Google Scholar 

  7. Shu-Hsien Liao, Personal Category Profiles for WWW Information Retrieval, Master Thesis, National Taiwan University, 1998.

    Google Scholar 

  8. Michael Li-Wei Lu, The Design and Implementation of Integrated User Interface for Web Browsing, Master Thesis, National Taiwan University, 1998.

    Google Scholar 

  9. Jakob Nielsen, User Interface Design for the WWW, ACM SIGCHI’97, 1997. Available through http://www.acm.org/sigchi/chi97/proceedings/tutorial/jn.htm (January 28, 1999).

  10. Stuart J. Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, Prentice-Hall International, Inc., 1995.

    Google Scholar 

  11. Gerard Salton, editor, The SMART Retrieval System: Experiments in Automatic Document Processing, Prentice-Hall Inc., 1971.

    Google Scholar 

  12. Gerard Salton, Automatic Text Processing: The Transformation, Analysis, and Retrieval of Information by Computer, Addison-Wesley, 1989.

    Google Scholar 

  13. Myaeng H. Sung and Robert R. Korfhage, Integration of User Profiles: Models and Experiments in Information Retrieval, Information Processing & Management, pp. 719–738, 1990.

    Google Scholar 

  14. Linda Tauscher and Saul Greenberg, Revisitation Patterns in World Wide Web Navigation, ACM SIGCHI’97, 1997. Available through http://www.acm.org/sigchi/chi97/proceedings/paper/sg.htm (January 28, 1999).

  15. Hsieh-Chang Tu and Jieh Hsiang, An Architecture and Category Knowledge for Intelligent Information Retrieval, the 31st Hawaii International Conference on System Sciences, HICSS-31, January 1998.

    Google Scholar 

  16. Hsieh-Chang Tu, Michael Li-Wei. Lu and Jieh Hsiang, Agent technology for website Browsing and Navigation, the 32nd Hawaii International Conference on System Sciences, HICSS-32, January 1999.

    Google Scholar 

  17. Bienvenido Velez, Ron Weiss, Mark A. Sheldon and David K. Gifford, Fast and Effective Query Refinement, ACM SIGIR’97, pp. 6–15, 1997.

    Google Scholar 

  18. Michael Wooldridge and Nicholas R. Jennings, Intelligent Agents: Theory and Practice, Knowledge Engineering Review, Vol. 10,No. 2, June 1995.

    Google Scholar 

  19. C. T. Yu, K. Lam and G. Salton, Term Weighting in Information Retrieval Using the Term Precision Model, Journal of the Association for Computing Machinery, JACM Vol. 29,No. 1, pp. 152–170, January 1982.

    MATH  MathSciNet  Google Scholar 

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© 1999 Springer-Verlag Berlin Heidelberg

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Hsiang, J., Tu, HC. (1999). Personalized Web Retrieval: Three Agents for Retrieving Web Information. In: Ishida, T. (eds) Multiagent Platforms. PRIMA 1998. Lecture Notes in Computer Science(), vol 1599. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48826-X_9

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  • DOI: https://doi.org/10.1007/3-540-48826-X_9

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-65967-9

  • Online ISBN: 978-3-540-48826-2

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