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Courses in summer term 2004 / Seminar on Recommender Systems / readings:
abstract readings presentations

List of readings (ee = link to electronic edition; ask me for the other references):

  1. Wed. 21.4. -- Introduction --
  2. Wed. 12.5. (M) Collaborative filtering. Speaker: Niklas Deutschmann
    1. John Breese, David Heckerman, Carl Kadie (1998): Empirical Analysis of Predictive Algorithms for Collaborative Filtering Proceedings of the Fourteenth Annual Conference on Uncertainty in Artificial Intelligence, Morgan Kaufmann, Madison, WI, USA, pp. 43-52.
    2. [ee] DaeEun Kim, Sea Woo Kim (2001): Dynamic Expert Group Models for Recommender Systems. In Ning Zhong, Yiyu Yao, Jiming Liu, Setsuo Ohsuga (eds.): Web Intelligence: Research and Development, First Asia-Pacific Conference, WI 2001, Maebashi City, Japan, October 23-26, 2001, Proceedings , Springer, pp. 136-140.
    3. [ee] Al Mamunur Rashid, Istvan Albert, Dan Cosley, Shyong K. Lam, Sean M. McNee, Joseph A. Konstan, John Riedl (2002): Getting to know you: learning new user preferences in recommender systems. IUI, pp. 127-134.
    4. [ee] Jonathan L. Herlocker, Joseph A. Konstan, Loren G. Terveen, John Riedl (2004): Evaluating collaborative filtering recommender systems. ACM Trans. Inf. Syst. 22/1, pp. 5-53.
  3. Wed. 19.5. (M) Content-based filtering and hybrid filtering methods. Speaker: Uli Siebold
    1. George Karypis (2000): Evaluation of item-based top-N recommendation algorithms .
    2. [ee] Robin D. Burke (2002): Hybrid Recommender Systems: Survey and Experiments. User Model. User-Adapt. Interact. 12/4, pp. 331-370.
    3. [ee] Meehee Lee, Pyungseok Choi, Yongtae Woo (2002): A Hybrid Recommender System Combining Collaborative Filtering with Neural Network. In Paul De Bra, Peter Brusilovsky, Ricardo Conejo (eds.): Adaptive Hypermedia and Adaptive Web-Based Systems, Second International Conference, AH 2002, Malaga, Spain, May 29-31, 2002, Proceedings , Springer, pp. 531-534.
    4. Joon Ho Park, Suyoung Yoon, Sangkyu Choe, Jinhan Kim (2001): Personalized Content Recommender System using a Hybrid Filtering Technique. In Wendy A. Lawrence-Fowler, Joachim Hasebrook (eds.): Proceedings of WebNet 2001 - World Conference on the WWW and Internet, Orlando, Florida, October 23-27, 2001 , AACE, pp. 989-990.
  4. Wed. 26.5. (M) Markov decision processes for modeling recommender systems. Speaker: Robert Mattmüller
    1. Guy Shani, Ronen I. Brafman, David Heckerman (2002): An MDP-based Recommender System. In Adnan Darwiche, Nir Friedman (eds.): UAI '02, Proceedings of the 18th Conference in Uncertainty in Artificial Intelligence, University of Alberta, Edmonton, Alberta, Canada, August 1-4, 2002 , Morgan Kaufmann, pp. 453-460.
    2. [ee] Ronen Brafman, David Heckerman, Guy Shani (2003): Recommendation as a Stochastic Sequential Decision Problem Proceedings of ICAPS 2003, Trento, Italy.
  5. Wed. 2.6. -- Whitsun break --
  6. Wed. 9.6. (M) profiling and implicit feedback Speaker: Axel Niese
    1. Diane Kelly, Jaime Teevan (2003): Implicit feedback for inferring user feedback: a bibliography .
  7. Wed. 16.6. (T) user models and ontologies. Speaker: Dominik Benz
    1. [ee] Stuart E. Middleton, Harith Alani, Nigel Shadbolt, David De Roure (2002): Exploiting Synergy Between Ontologies and Recommender Systems. In Martin Frank, Natasha Noy, Steffen Staab (eds.): Proceedings of the WWW2002 International Workshop on the Semantic Web, Hawaii, May 7, 2002 .
    2. [ee] Stuart E. Middleton, David De Roure, Nigel Shadbolt (2001): Capturing knowledge of user preferences: ontologies in recommender systems. In Proceedings of the First International Conference on Knowledge Capture (K-CAP 2001), October 21-23, 2001, Victoria, BC, Canada , ACM, pp. 100-107.
    3. [ee] Stuart E. Middleton, Nigel Shadbolt, David De Roure (2004): Ontological user profiling in recommender systems. ACM Trans. Inf. Syst. 22/1, pp. 54-88.
  8. Wed. 23.6. (M) recommender systems and network theory (hubs and authorities). Speaker: Alexandru Cocora.
    1. [ee] Jon M. Kleinberg (1999): Authoritative sources in a hyperlinked environment Journal of the ACM 46/5, pp. 604-632.
    2. [ee] Lawrence Page, Sergey Brin, Rajeev Motwani, Terry Winograd (1998): The PageRank Citation Ranking: Bringing Order to the Web .
  9. Fr. 25.6. 14:00-15:30 (M) recommender systems and social choice theory. Speaker: Frederik Löser
    1. David M. Pennock, Eric Horvitz, C. Lee Giles (2000): Social Choice Theory and Recommender Systems: Analysis of the Axiomatic Foundations of Collaborative Filtering. In Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on on Innovative Applications of Artificial Intelligence, July 30 - August 3, 2000, Austin, Texas, USA. , AAAI Press / The MIT Press, pp. 729-734.
    2. A. Taylor (1995): Mathematics and Politics: Strategy, Voting, Power, and Proof , Springer-Verlag, New York.
  10. Fr. 25.6. 15:30-17:00 (T) Adaptive web sites, assisted browsing, and web caching and prefetching. Speaker: Sandra Busl.
    1. M. Perkowitz, O. Etzioni (1998): Adaptive Web Sites, Automatically Synthesizing Web Pages Proceedings of the Fifteenth National Conference on Artificial Intelligence (AAAI'98), Madison, WI, pp. 727-732.
    2. X. Fu, J. Budzik, K. J. Hammond (2000): Mining Navigation History for Recommendation Proceedings of the 2000 International Conference on Intelligent User Interfaces, New Orleans, LA, January, ACM, pp. 106-112.
    3. Wolfgang Gaul, Lars Schmidt-Thieme (2002): Recommender Systems Based on User Navigational Behavior in the Internet Behaviormetrika 29, pp. 1-22.
  11. --- (M) Graph-based Recommender-Systems.
    1. Zan Huang, Hsinchun Chen, Daniel Zeng (2004): Applying Associative Retrieval Techniques to Alleviate the Sparsity Problem in Collaborative Filtering ACM Transactions on Information Systems 22/1, pp. 116-142.
    2. Zan Huang, Wingyan Chung, Hsinchun Chen (2004): A graph model for E-commerce recommender systems Journal of the American Society for Information Science and Technology 55/3, pp. 259-274.
    3. [ee] Charu Aggarwal, Joel Wolf, Kun-Lung Wu, Philip Yu (1999): Horting Hatches an Egg: A New Graph-theoretic Approach to Collaborative Filtering Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, ACM Press, San Diego, CA, USA, pp. 201-212.
  12. Wed. 30.6. (M) conditional preference nets (CP-nets). Speaker: Bernd Gutmann.
    1. Craig Boutilier, Ronen I. Brafman, Carmel Domshlak, Holger H. Hoos, David Poole (2004): CP-nets: A Tool for Representing and Reasoning with Conditional Ceteris Paribus Preference Statements Journal of Artificial Intelligence Research 21, pp. 135-191.
    2. Ronen I. Brafman, Yannis Dimopoulos (2003): Extended Semantics and Optimization Algorithms for CP-networks .
  13. Wed. 7.7. (T) Recommender systems in digital libraries and e-learning. Speaker: Miao Yi
    1. [ee] Dan Cosley, Steve Lawrence, David M. Pennock (2002): REFEREE: An Open Framework for Practical Testing of Recommender Systems using ResearchIndex. VLDB, pp. 35-46.
    2. [ee] Andreas Geyer-Schulz, Michael Hahsler (2002): Comparing Two Recommender Algorithms with the Help of Recommendations by Peers. In Osmar R. Zaïane, Jaideep Srivastava, Myra Spiliopoulou, Brij M. Masand (eds.): WEBKDD 2002 - MiningWeb Data for Discovering Usage Patterns and Profiles, 4th International Workshop, Edmonton, Canada, July 23, 2002, Revised Papers , Springer, pp. 137-158.
    3. [ee] Andreas Geyer-Schulz, Michael Hahsler, Maximillian Jahn (2001): A Customer Purchase Incidence Model Applied to Recommender Services. In Ron Kohavi, Brij M. Masand, Myra Spiliopoulou, Jaideep Srivastava (eds.): WEBKDD 2001 - Mining Web Log Data Across All Customers Touch Points, Third International Workshop, San Francisco, CA, USA, August 26, 2001, Revised Papers , Springer, pp. 25-47.
    4. Andreas Geyer-Schulz, Andreas Neumann, Anke Thede (2003): Others Also Use: A Robust Recommender System for Scientific Libraries. In Traugott Koch, Ingeborg Sølvberg (eds.): Research and Advanced Technology for Digital Libraries, 7th European Conference, ECDL 2003, Trondheim, Norway, August 17-22, 2003, Proceedings , Springer, pp. 113-125.
  14. Wed. 14.7. no seminar.
    --- (T) electronic program guides in digital tv.
    1. Srinivas Gutta, Kaushal Kurapati, K. P. Lee, Jacquelyn Martino, John Milanski, J. David Schaffer, John Zimmerman (2000): TV Content Recommender System. In Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on on Innovative Applications of Artificial Intelligence, July 30 - August 3, 2000, Austin, Texas, USA. , AAAI Press / The MIT Press, pp. 1121-1122.
    2. John Zimmermann, Kaushal Kurapati, Anna L. Buczak, Dave Schaffer, Srinivas Gutta, Jacquelyn Martino (2004): TV personalization system - design of a tv show recommender engine and interface .
  15. Wed. 21.7. (T) Recommender systems in e-commerce. Speaker: Christine Preisach
    1. [ee] J. Ben Schafer, Joseph A. Konstan, John Riedl (1999): Recommender systems in e-commerce. ACM Conference on Electronic Commerce, pp. 158-166.
    2. K. Srikumar, B. Bhasker (2004): Personalized Recommendations in E-Commerce 5th World Congress on Management of Electronic Business in 25th McMaster World Congress, Ontario, Canada, Jan. 2004.