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Abstract

Research on recommender systems has primarily addressed centralized scenarios and largely ignored open, decentralized systems where remote information distribution prevails. The absence of superordinate authorities having full access and control introduces some serious issues requiring novel approaches and methods. Hence, our primary objective targets the successful deployment and integration of recommender system facilities for Semantic Web applications, making use of novel technologies and concepts and incorporating them into one coherent framework.

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References

  1. Abdul-Rahman, A., Hailes, S.: A distributed trust model. In: New Security Paradigms Workshop, Cumbria, UK, pp. 48–60 (September 1997)

    Google Scholar 

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

    Article  Google Scholar 

  3. Berscheid, E.: Interpersonal attraction. In: Gilbert, D., Fiske, S., Lindzey, G. (eds.) The Handbook of Social Psychology, 4th edn., vol. II, McGraw-Hill, New York (1998)

    Google Scholar 

  4. Beth, T., Borcherding, M., Klein, B.: Valuation of trust in open networks. In: Gollmann, D. (ed.) ESORICS 1994. LNCS, vol. 875, pp. 3–18. Springer, Heidelberg (1994)

    Google Scholar 

  5. Golbeck, J., Parsia, B., Hendler, J.: Trust networks on the Semantic Web. In: Klusch, M., Omicini, A., Ossowski, S., Laamanen, H. (eds.) CIA 2003. LNCS (LNAI), vol. 2782, pp. 238–249. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  6. Goldberg, D., Nichols, D., Oki, B., Terry, D.: Using collaborative filtering to weave an information tapestry. Communications of the ACM 35(12), 61–70 (1992)

    Article  Google Scholar 

  7. Huang, Z., Chung, W., Ong, T.-H., Chen, H.: A graph-based recommender system for digital library. In: Proceedings of the Second ACM/IEEE-CS Joint Conference on Digital Libraries, Portland, OR, USA, pp. 65–73. ACM Press, New York (2002)

    Chapter  Google Scholar 

  8. Jensen, C., Davis, J., Farnham, S.: Finding others online: Reputation systems for social online spaces. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Minneapolis, MN, USA, pp. 447–454. ACM Press, New York (2002)

    Google Scholar 

  9. Kautz, H., Selman, B., Shah, M.: Referral Web: Combining social networks and collaborative filtering. Communications of the ACM 40(3), 63–65 (1997)

    Article  Google Scholar 

  10. Levien, R., Aiken, A.: Attack-resistant trust metrics for public key certification. In: Proceedings of the 7th USENIX Security Symposium, San Antonio, TX, USA (January 1998)

    Google Scholar 

  11. Marsh, S.: Formalising Trust as a Computational Concept. PhD thesis, Department of Mathematics and Computer Science, University of Stirling, Stirling, UK (1994)

    Google Scholar 

  12. Massa, P., Bhattacharjee, B.: Using trust in recommender systems: An experimental analysis. In: Jensen, C., Poslad, S., Dimitrakos, T. (eds.) iTrust 2004. LNCS, vol. 2995, pp. 221–235. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  13. Middleton, S., Alani, H., Shadbolt, N., De Roure, D.: Exploiting synergy between ontologies and recommender systems. In: Proceedings of the WWW2002 International Workshop on the Semantic Web. CEUR Workshop Proceedings, Maui, HW, USA, vol. 55 (May 2002)

    Google Scholar 

  14. Miller, B., Albert, I., Lam, S., Konstan, J., Riedl, J.: MovieLens unplugged: Experiences with an occasionally connected recommender system. In: Proceedings of the ACM 2003 Conference on Intelligent User Interfaces (Accepted Poster), Chapel Hill, NC, USA. ACM, New York (2003)

    Google Scholar 

  15. Olsson, T.: Bootstrapping and Decentralizing Recommender Systems. PhD thesis, Uppsala University, Uppsala, Sweden (2003)

    Google Scholar 

  16. O’Mahony, M., Hurley, N., Kushmerick, N., Silvestre, G.: Collaborative recommendation: A robustness analysis. ACM Transactions on Internet Technology 4(3) (August 2004)

    Google Scholar 

  17. Page, L., Brin, S., Motwani, R., Winograd, T.: The PageRank citation ranking: Bringing order to the Web. Technical report, Stanford Digital Library Technologies Project (1998)

    Google Scholar 

  18. Quillian, R.: Semantic memory. In: Minsky, M. (ed.) Semantic Information Processing, pp. 227–270. MIT Press, Boston (1968)

    Google Scholar 

  19. Schafer, B., Konstan, J., Riedl, J.: Recommender systems in e-commerce. In: Proceedings of the 1st ACM Conference on Electronic Commerce, Denver, CO, USA, pp. 158–166. ACM Press, New York (1999)

    Chapter  Google Scholar 

  20. Shardanand, U., Maes, P.: Social information filtering: Algorithms for automating “word of mouth”. In: Proceedings of the ACM CHI 1995 Conference on Human Factors in Computing Systems, vol. 1, pp. 210–217 (1995)

    Google Scholar 

  21. Sinha, R., Swearingen, K.: Comparing recommendations made by online systems and friends. In: Proceedings of the DELOS-NSF Workshop on Personalization and Recommender Systems in Digital Libraries, Dublin, Ireland (June 2001)

    Google Scholar 

  22. Ziegler, C.-N., Lausen, G.: Analyzing correlation between trust and user similarity in online communities. In: Jensen, C., Poslad, S., Dimitrakos, T. (eds.) iTrust 2004. LNCS, vol. 2995, pp. 251–265. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  23. Ziegler, C.-N., Lausen, G.: Spreading activation models for trust propagation. In: Proceedings of the IEEE International Conference on e-Technology, e-Commerce, and e-Service, Taipei, Taiwan. IEEE Computer Society Press, Los Alamitos (2004)

    Google Scholar 

  24. Ziegler, C.-N., Lausen, G., Schmidt-Thieme, L.: Taxonomy-driven computation of product recommendations (submitted for publication, 2004)

    Google Scholar 

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Ziegler, CN. (2004). Semantic Web Recommender Systems. In: Lindner, W., Mesiti, M., Türker, C., Tzitzikas, Y., Vakali, A.I. (eds) Current Trends in Database Technology - EDBT 2004 Workshops. EDBT 2004. Lecture Notes in Computer Science, vol 3268. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30192-9_8

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  • DOI: https://doi.org/10.1007/978-3-540-30192-9_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23305-3

  • Online ISBN: 978-3-540-30192-9

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