Enhancing collaborative filtering by frequent usage patterns

1st International Conference on the Applications of Digital Information and Web Technologies, ICADIWT 2008

Volumn , Issue , 2008, Pages 180-185

  Esslimani, Ilham ^a   Brun, Armelle ^a   Boyer, Anne ^a  

^a LORIA   (France)

Author keywords

[No Author keywords available]

Indexed keywords

COMBINES; FORECASTING; INFORMATION RETRIEVAL SYSTEMS; INFORMATION SERVICES; MANAGEMENT INFORMATION SYSTEMS; SIGNAL FILTERING AND PREDICTION;

COLLABORATIVE FILTERING; FREQUENT PATTERNS; NEW TECHNIQUES; PEARSON CORRELATIONS; PERSONALIZATION; RECOMMENDER SYSTEMS; USAGE PATTERNS; WEB SITES; WEB USAGE PATTERNS;

INFORMATION RETRIEVAL;

EID: 57949116791     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICADIWT.2008.4664341     Document Type: Conference Paper

References (12)

1. G. Adomavicius and A. Tuzhilin, "Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art", IEEE transactions on knowledge and data engineering, IEEE Educational Activities Department, NJ, USA ,2005, 17(6), pp. 734-749.
2. B. Mobasher, "Data Mining for Web Personaiizatuon", The Adaptive Web: Methods and Strategies of Web Personalization, Lecture Notes in Computer Science, Springer-Verlag, Berlin, Germany, 2007, vol. 4321, pp. 1-27.
3. J. B. Schafer, D. Frankowski, J. L. Herlocker and S. Sen, "Collaborative filtenng recommender systems", The Adaptive Web: Methods and Strategies of Web Personalization, Lecture Notes in Computer Science, Spnnger-Verlag, Berlin, Germany, 2007, vol. 4321, pp. 291-324.
4. E. Magdalini, V. Miclialis and K. Dimitris, "Web path recommendations based on page ranking and markov models", Proceedings of the 7th annual ACM international workshop on Web information and data management, ACM Press, New York, USA, 2005, pp. 2-9.
5. R. Burke, "Hybrid Recommender Systems: Survey and Experiments", User Modeling and User-Adapted Interaction, Kluwer Academic Publishers, Hingham, USA, 2002, 12(4), pp. 331-370.
6. N. Golovin, and E. Rahm, "Reinforcement Learning Architecture fur Web Recommendations", Proceedings of the International Conference on Information Technology: Coding and Computing ITCC'04, IEEE Computer Society, Washington DC, USA , 2004, pp. 398-402.
7. M. Han, I. King and M.R. Lyo, "Effective missing data prediction for collaborative filtering", Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval, ACM Press, New York, 2007, pp. 39-46.
8. L. Baltrunas and F. Ricci, "Dynamic item weighting and selection for collaborative filtering", Web mining 2.0 Workshop, ECML-PKDD 2007 , Springer-Verlag, Berlin, Germany, 2007, pp.135-145.
9. M. O'Mahony, N Hurley, N. Kushmerick and S. Guénolé, "Collaborative recommendation : A robustness analysis", ACM Transactions on Internet Technology (TOIT), ACM Press, New York, USA, 2004, Issue 4, pp. 344-377.
10. P. Viappiani, B. Faltings and P. Pu, "Preference-based Search using Example-Critiquing with Suggestions", Journal of artificial intelligence Research, AAAI Press, vol. 27, 2006, pp. 465-503.
11. B.Mobasher, H. Dai, T. Luo and M. Nakagawa, "Improving the effectiveness of collaborative filtering on anonymous web usage data", Proceedings of the workshop of intelligent techniques for web personalization, 2001, pp. 53-60.
12. M. Degemmis,P. Lops and G. Semeraro, "A content-collaborative recommender that exploits WordNet-based user profiles for neighborhood formation", User Modeling and User-Adapted Interaction, Kluwer Academic Publishers ,17(3), 2007, pp 217-255.