Skip to main content

A Formal Framework for Combining Evidence in an Information Retrieval Domain

  • Conference paper
Knowledge-Based Intelligent Information and Engineering Systems (KES 2003)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2773))

  • 1181 Accesses

Abstract

This paper presents a formal framework for the combination of multiple sources of evidence in an information retrieval domain. Previous approaches which have included additional information and evidence have primarily done so in an ad-hoc manner. In the proposed framework, collaborative and content information regarding both the document data and the user data is formally specified. Furthermore, the notion of user sessions is included in the framework. A sample instantiation of the framework is provided.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 74.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 99.00
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Baeza-Yates, R., Ribeiro-Neto, B.: Modern Information Retrieval. ACM Press, New York (1999)

    Google Scholar 

  2. Balabanovic, M., Shoham, Y.: Fab: Content-based, collaborative recommendation. Communications of the ACM 40(3), 66–72 (1997)

    Article  Google Scholar 

  3. Basu, C., Hirsh, H., Cohen, W.: Recommendation as classification: Using social and content-based information in recommendation. In: Proceedings of the Fifteenth National Conference on Artificial Intelligence (AAAI 1998), pp. 714–721. AAAI Press, Menlo Park (1998)

    Google Scholar 

  4. Claypool, M., Gokhale, A., Miranda, T., Murnikov, P., Netes, D., Sartin, M.: Combining content-based and collaborative filters in an online newspaper. In: Online Proceedings of the ACM SIGIR 1999 Workshop on Recommender Systems: Algorithms and Evaluation, University of California, Berkeley (1999)

    Google Scholar 

  5. Croft, W.B.: Combining approaches to information retrieval. Kluwer Academic Publishers, Dordrecht (2000)

    Google Scholar 

  6. Dominich, S.: Mathematical Foundations of Information Retrieval. Kluwer Academic Publishers, Dordrecht (2001)

    Book  MATH  Google Scholar 

  7. Fisk, D.: An application of social filtering to movie recommendation. In: Nwana, H.S., Azarmi, N. (eds.) Software Agents and Soft Computing. Springer, Heidelberg (1997)

    Google Scholar 

  8. Griffith, J., O’Riordan, C.: Non-traditional collaborative filtering techniques. Technical report, Dept. of Information Technology, NUI, Galway, Ireland (2002)

    Google Scholar 

  9. Jin, R., Dumais, S.: Probabilistic combination of content and links. In: Proceedings of the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 402–403 (2001)

    Google Scholar 

  10. Resnick, P., Iacovou, N., Suchak, M., Bergstrom, P., Riedl, J.: Grouplens: An open architecture for collaborative filtering of netnews. In: Proceedings of ACM 1994 Conference on CSCW, pp. 175–186. Chapel Hill (1994)

    Google Scholar 

  11. C. O’ Riordan and H. Sorensen. Multi-agent based collaborative filtering. In M. Klusch et al. (eds) Cooperative Information Agents 1999. Lecture Notes in Artificial Intelligence (1999)

    Google Scholar 

  12. Ruthven, I., Lalmas, M.: Selective relevance feedback using term characteristics. In: Proceedings of the 3rd International Conference on Coceptions of Library Information Science, CoLIS 3 (1999)

    Google Scholar 

  13. Turtle, H.R., Croft, W.B.: Evaluation of an inference network-based retrieval model. ACM Trans. on Info. Systems 3 (1991)

    Google Scholar 

  14. van Rijsbergen, C.J.: Towards an information logic. In: ACM SIGIR Conference on Research and Development in Information Retrieval (1989)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2003 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Griffith, J., O’Riordan, C. (2003). A Formal Framework for Combining Evidence in an Information Retrieval Domain. In: Palade, V., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2003. Lecture Notes in Computer Science(), vol 2773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45224-9_115

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-45224-9_115

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40803-1

  • Online ISBN: 978-3-540-45224-9

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics