A hybrid, multi-dimensional recommender for journal articles in a scientific digital library

Proceedings - 2007 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT Workshops 2007

Volumn , Issue , 2007, Pages 111-114

  Vellino, André ^a   Zeber, David ^b  

^a NATIONAL RESEARCH COUNCIL CANADA   (Canada)

^b Department of Molecular Biology and Genetics   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COLLABORATIVE FILTERING; INTELLIGENT AGENT TECHNOLOGY; INTERNATIONAL CONFERENCES; JOURNAL ARTICLES; MULTI-DIMENSIONAL; MULTIPLE DIMENSIONS; RECOMMENDER SYSTEMS; SCHOLARLY ARTICLES; WEB INTELLIGENCE;

CHLORINE COMPOUNDS; DIGITAL ARITHMETIC; LIBRARIES; METADATA; TECHNOLOGY;

DIGITAL LIBRARIES;

EID: 48149104243     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/WIIATW.2007.4427552     Document Type: Conference Paper

References (30)

1. G. Adomavicius, R. Sankaranarayanan, S. Sen, and A. Tuzhilin. Incorporating Contextual. Information inRecommender Systems Using a Multidimensional Approach. ACM Trans. Inf. Syst., 23(1):103-145, 2005.
2. S. Ananiadou and E. John McNaught. Text Mining for Biology and Biomedicine. Artech House, Boston, 2006.
3. M. Anderson, M. Ball, H. Boley, S. Greene, N. Howse, D. Lemire, and S. McGrath. RACOFI: a Rule-Applying Collaborative Filtering System. In Proceedings of COLA '03. IEEE/WIC, October 2003.
4. H. Avancini, L. Candela, and U. Straccia. Recommenders In A Personalized, Collaborative Digital. Library Environment. Journal of Intelligent Information Systems, 27(1), 2007.
5. R. Baeza-Yates, C. Hurtado, and M. Mendoza. Query Recommendation Using Query Logs in Search Engines. International Workshop on Clustering Information over the Web (ClustWeb, in conjunction with EDBT), Crete, Greece, March (to flapper in LNCS), 2004.
6. V. Batagelj. Efficient Algorithms for Citation Network Analysis. Arxiv preprint cs.DL/0309023, 2003.
7. J. Breese, D. Heckerman, C. Kadie, et al. Empirical Analysis of Predictive Algorithms for Collaborative Filtering. Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, 461, 1998.
8. S. Brin and L. Page. The anatomy of a large-scale hypertextual Web search engine. Computer Networks and ISDN Systems, 30(1.-7): 107-117, 1998.
9. R. Burke. Hybrid Recommender Systems: Survey and Experiments. User Modeling and User-Adapted Interaction, 12(4):331-370, 2002.
10. B. Dumouchel and J. Demaine. Knowledge Discovery in the Digital Library: Access Tools for Mining Science. Information Services and Use, 26(1):39-44, 2006.
11. M. Garden and G. Dudek. Mixed Collaborative and Content-Based Filtering with User-Contributed Semantic Features. In Proceedings of the 21st AAAI National Conference on Artificial Intelligence (AAAI'06), Boston, Massachusetts, July 2006.
12. J. L. Herlocker, J. A. Konstan, and J. Riedl. Explaining Collaborative Filtering Recommendations. In CSCW '00: Proceedings of the 2000 ACM Conference on Computer Supported Cooperative Work, pages 241-250, New York, NY, USA, 2000. ACM Press.
13. S. Hwang. A Prototype WWW Literature Recommendation System, for Digital Libraries San-Yih Hwang, Wen-Chiang Hsiung, Wan-Shiou Yang The Authors. Online Information Review, 27(3): 169-182, 2003.
14. J. Konstan, S. McNee, C.-N. Ziegler, R. Torres, N. Kapoor, and J. Riedl. Lessons on Applying Automated Recommender Systems to Information-Seeking Tasks. In Proceedings of the Twenty-First National Conference on Artificial Intelligence, Boston, MA, USA, July 2006.
15. D. Lemire and A. Maclachlan. Slope One Predictors for Online Rating-Based Collaborative Filtering. In Proceedings of SIAM Data Mining (SDM'05), 2005.
16. K. McCarthy, J. Reilly, L. McGinty, and B. Smyth. Thinking Positively-Explanatory Feedback for Conversational Recommender Systems. Proceedings of the European Conference on Case-Based Reasoning (ECCBR-04) Explanation Workshop, pages 115-124, 2004.
17. S. McNee, I. Albert, D. Cosley, P. Gopalkrishnan, S. Lam, J. Konstan, and J. Riedl. On the Recommending of Citations for Research Papers. Proceedings of the 2002 ACM Conference on Computer Supported Cooperative work, pages 116-125, 2002.
18. S. M. McNee, N. Kapoor, and J. A. Konstan. Don't Look Stupid: Avoiding Pitfalls when Recommending Research Papers. In CSCW '06: Proceedings of the 2006 20th Anniversary Conference on Computer Supported Cooperative Work, pages 171-180, New York, NY, USA, 2006. ACM Press.
19. S. Pohl, F. Radlinski, and T. Joachims. Recommending Related Papers Based on Digital Library Access Records. ACM/IEEE Joint Conference on Digital Libraries, JCDL 2007, Vancouver, B.C., Canada, June 18-23, 2007.
20. P. Pu and L. Chen. Trust Building with Explanation Interfaces. In IUI '06: Proceedings of the 11th International Conference On Intelligent User Interfaces, pages 93-100, New York, NY, USA, 2006. ACM Press.
21. C. Shahabi, F. Banaei-Kashani, Y. Chen, and D. McLeod. Yoda: An Accurate and Scalable Web-based Recommendation System. Sixth International Conference on Cooperative Information Systems (CoopIS 2001), Trento, Italy, September, 2001.
22. R. Sinha and K. Swearingen. The Role of Transparency in Recommender Systems. Conference on Human Factors in Computing Systems, pages 830-831, 2002.
23. A. F. Smeaton and J. Callan. Personalisation and Recommender Systems in Digital Libraries. International Journal on Digital Libraries, V5(4):299-308, 2005.
24. M. Smith. Scientific Research Communication: The Promise and Current Realities of Enhanced Publications. http://www.spatial.maine.edu/icfs/Smith white paper 2006.pdf, 2006.
25. M. Y. Symeonidis P., Nanopoulos A. Feature-weighed user model for recommender systems. In Proceedings of the UM 2007 conference, pages 97-107, Corfu, 2007.
26. Thorsten Joachims and Laura Granka and Bing Pan and Helene Hembrooke and Filip Radlinski. and Geri Gay. Evaluating The Accuracy of Implicit Feedback from Clicks and. Query Reformulations in Web search. ACM Trans. Inf. Syst., 25(2):7, 2007.
27. R. Torres, S. McNee, M. Abel, J. Konstan, and J. Riedl. Enhancing Digital. Libraries with TechLens+. Proceedings of the 2004 Joint ACM/EEE Conference on Digital Libraries, pages 228-236, 2004.
28. J. Wang, A. de Vries, and M. Reinders. Unifying User-Based and Item-Based Collaborative Filtering Approaches by Similarity Fusion. Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 501-508, 2006.
29. J. Webster, S. Jung, and J. Herlocker. Collaborative Filtering: a New Approach to Searching Digital Libraries. New Review of Information Networking, 10(2):177-191, 2004.
30. Y. Zhang, J. Callan, and T. Minka. Novelty and Redundancy Detection in Adaptive Filtering. In SIGIR '02: Proceedings of the 25th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 81.-88, New York, NY, USA, 2002. ACM Press.