Skip to main content

Peer-Based Relay Scheme of Collaborative Filtering for Research Literature

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7044))

Abstract

Much work has been done in both industry and academia on filtering for research literature, however most existing studies have their limitations in coping with the inherent characteristics of research literature search, i.e., most articles attract very few readers among all the researchers, and the recommendations are often circulated through members of particular communities. In this paper we propose a peer-based relay scheme of collaborative filtering for, but not limited to research literature. In the scheme, a recommendation request is relayed through a social structure dynamically formed by co-peers with common interests, and the recommendation results are adjusted and propagated by the co-peers. A hybrid filtering approach is deployed in the scheme.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
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

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Adomavicius, G., Tuzhilin, A.: Toward the next generation of recommender systems: A survey of the State-of-the-Art and possible extensions. IEEE Trans. on Knowl. and Data Eng. 17(6), 734–749 (2005)

    Article  Google Scholar 

  2. Baeza-Yates, R., Ribeiro-Neto, B., et al.: Modern information retrieval, vol. 463. ACM press, New York (1999)

    Google Scholar 

  3. Belkin, N.J., Croft, W.B.: Information filtering and information retrieval: two sides of the same coin? Communications of the ACM 35(12), 29–38 (1992)

    Article  Google Scholar 

  4. Berkovsky, S., Busetta, P., Eytani, Y., Kuflik, T., Ricci, F.: Collaborative Filtering over Distributed Environment. In: DASUM Workshop, Citeseer (2005)

    Google Scholar 

  5. Burke, R.: Hybrid recommender systems: Survey and experiments. User Modeling and User-Adapted Interaction 12(4), 331–370 (2002)

    Article  MATH  Google Scholar 

  6. Geyer-Schulz, A., Hahsler, M., Neumann, A., Thede, A.: Behavior-Based Recommender Systems as Value-Added Services for Scientific Libraries

    Google Scholar 

  7. Goldberg, K., Roeder, T., Gupta, D., Perkins, C.: Eigentaste: A Constant Time Collaborative Filtering Algorithm. Information Retrieval 4(2), 133–151 (2001)

    Article  MATH  Google Scholar 

  8. ISI-WoK (2010), http://wokinfo.com/

  9. Jung, S., Kim, J., Herlocker, J.L.: Applying collaborative filtering for efficient document search. In: IEEE/WIC/ACM International Conference on Web Intelligence, pp. 640–643. IEEE Computer Society (2004)

    Google Scholar 

  10. Lemire, D., Maclachlan, A.: Slope one predictors for online Rating-Based collaborative filtering. Society for Industrial Mathematics (2005)

    Google Scholar 

  11. McNee, S.M., Albert, I., Cosley, D., Gopalkrishnan, P., Lam, S.K., Rashid, A.M., Konstan, J.A., Riedl, J.: On the recommending of citations for research papers. In: ACM Conference on Computer Supported Cooperative Work, New Orleans, Louisiana, USA, pp. 116–125. ACM (2002)

    Google Scholar 

  12. Pohl, S., Radlinski, F., Joachims, T.: Recommending related papers based on digital library access records. In: ACM/IEEE-CS Joint Conference on Digital Libraries, pp. 417–418. ACM (2007)

    Google Scholar 

  13. Redner, S.: How popular is your paper? An empirical study of the citation distribution. The European Physical Journal B 4(2), 131–134 (1998)

    Article  Google Scholar 

  14. Resnick, P., Iacovou, N., Suchak, M., Bergstrom, P., Riedl, J.: GroupLens: an open architecture for collaborative filtering of netnews. In: ACM Conference on Computer Supported Cooperative Work, pp. 175–186. ACM (1994)

    Google Scholar 

  15. Shardanand, U., Maes, P.: Social information filtering: algorithms for automating word-of-mouth. In: SIGCHI Conference on Human Factors in Computing Systems, pp. 210–217. ACM Press/Addison-Wesley Publishing Co. (1995)

    Google Scholar 

  16. Tveit, A.: Peer-to-peer based recommendations for mobile commerce. In: International Workshop on Mobile Commerce, Rome, Italy, pp. 26–29. ACM (2001)

    Google Scholar 

  17. Wu, H.C., Luk, R.W.P., Wong, K.F., Kwok, K. L.: A retrospective study of a hybrid document-context based retrieval model. Information Processing and Management: an International Journal 43(5), 1308–1331 (2007)

    Article  Google Scholar 

  18. Wu, H.C., Luk, R.W.P., Wong, K.F., Kwok, K.L.: Interpreting TF-IDF term weights as making relevance decisions. ACM Transactions on Information Systems (TOIS) 26(3), 1–37 (2008)

    Article  Google Scholar 

  19. Zhang, Z.K., Zhou, T., Zhang, Y.C.: Personalized recommendation via integrated diffusion on user-item-tag tripartite graphs. Physica A Statistical Mechanics and its Applications 389, 179–186 (2010)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Zhong, Y., Zhao, W., Yang, J., Xu, L. (2011). Peer-Based Relay Scheme of Collaborative Filtering for Research Literature. In: Meersman, R., et al. On the Move to Meaningful Internet Systems: OTM 2011. OTM 2011. Lecture Notes in Computer Science, vol 7044. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25109-2_21

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-25109-2_21

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25108-5

  • Online ISBN: 978-3-642-25109-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics