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Courses in winter term 2006/7 / Seminar on Recommender Systems and Personalization / readings:
readings

Note on Seminar Paper :

  • Due four weeks after end of term (Monday, 12.03.07),
  • 30 pages at most,
  • 3 hard copies(printed) and 1 soft copy (CD).
  • Note on Grades:
  • Marks will be based on presentation (including answers to questions),seminar paper, and general participation (e.g., asking questions),
  • bonuses for own experiments or implementations. If any, please also include in the CD.
  • List of readings (ee = link to electronic edition; ask me for the other references):

    1. -- Introduction --
    2. (T) Recommeder System Introduction and Application.
      1. [ee] J. Ben Schafer, Joseph A. Konstan, John Riedl (1999): Recommender systems in e-commerce ACM Conference on Electronic Commerce[ee] J. Ben Schafer, Joseph A. Konstan, John Riedl (1999): Recommender systems in e-commerce. ACM Conference on Electronic Commerce, pp. 158-166158-166.
      2. [ee] Jonathan L. Herlocker, Joseph A. Konstan, Loren G. Terveen, John Riedl (2004): Evaluating collaborative filtering recommender systems. ACM Trans. Inf. Syst. 22/1[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. 5-535-53.

      3. Further Reading (optionally):
      4. 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.
      5. L. Terveen, W. Hill (2001): Beyond Recommender Systems: Helping People Help Each Other Carroll, J. (ed.), HCI in the New Millennium. Addison Wesley.
    3. Tue. 05.12 (M) Time issues in Recommender Systems. Speaker: Maik Warblow
      1. Yi Ding, Xue Li, Maria E. Orlowska (2006): Recency-based collaborative filtering CRPITS'49: Proceedings of the 49th conference on Database technologies 2006, ACM Press, pp. 99--107.

      2. Further Reading (optionally):
      3. Sinan Zhan, Fengrong Gao, Chunxiao Xing, Lizhu Zhou (2006): Addressing Concept Drift problem in collaborative filtering systems Proceedings of ECAI 2006 Workshop on Recommender Systems, Riva del Garda, Italy.
      4. [ee] Yi Ding, Xue Li (2005): Time weight collaborative filtering CIKM '05: Proceedings of the 14th ACM international conference on Information and knowledge management, ACM Press, pp. 485--492.
      5. [ee] Tiffany Ya Tang, Pinata Winoto, Keith C. C. Chan (2003): On the Temporal Analysis for Improved Hybrid Recommendations WI '03: Proceedings of the IEEE/WIC International Conference on Web Intelligence, IEEE Computer Society.
    4. Tue. 12.12 (M) Sentiment analysis in Recommender System. Speaker: Markus Kiesau
      1. C.W.K. Leung , S.C.F. Chan, F.L. Chung (2006): Integrating Collaborative Filtering and Sentiment Analysis: A Rating Inference Approach Proceedings of ECAI 2006 Workshop on Recommender Systems, Riva del Garda, Italy, pp. 62--66.
      2. [ee] Bo Pang , Lillian Lee (2005): Seeing stars: Exploiting class relationships for sentiment categorization with respect to rating scales Proceedings of ACL 2005 , pp. 115--124.

      3. Further Reading (optionally):
      4. [ee] Michael Fleischman, Eduard Hovy (2003): Recommendations without user preferences: a natural language processing approach Proceedings of the 8th international conference on Intelligent user interfaces, ACM Press, pp. 242--244.
    5. Tue. 26.12 -- Winter break --
    6. Tue. 02.01 -- Winter break --
    7. Tue. 09.01 (T) Implicit Feedback. Speaker: Bendad Thomas
      1. Alexander Birukov, Enrico Blanzieri, Paolo Giorgini (2005): Implicit: a recommender system that uses implicit knowledge to produce suggestions Technical Report DIT-05-038, Informatica e Telecomunicazioni, University of Trento.

      2. Further Reading (optionally):
      3. [ee] Diane Kelly, Jaime Teevan (2003): Implicit feedback for inferring user preference: a bibliography SIGIR Forum, pp. 18-28.
      4. S. Gadanho (2006): TV Recommendations based on Implicit Information Proceedings of the ECAI 2006 Workshop on Recommender Systems.
    8. Tue. 16.01 (M) Semantic web Personalization. Speaker: Nadine Heinrichs
      1. A. Loizou, S.Dasmahapatra (2006): Recommender Systems for the Semantic Web ECAI 2006 Recommender Systems Workshop (in press), Trento, Italy.

      2. Further Reading (optionally):
      3. T. Heath, E. Motta (2006): Personalizing Relevance on the Semantic Web through Trusted Recommendations from a Social Network Workshop: Semantic Web Personalization, 3rd European Semantic Web Conference (ESWC2006), Budva, Montenegro.
      4. Ph. Mylonas, D. Vallet, M. Fernández, P. Castells, Y. Avrithis (2006): Ontology-based Personalization for Multimedia Content Workshop: Semantic Web Personalization, 3rd European Semantic Web Conference (ESWC2006), Budva, Montenegro.
      5. Jochen Fischer, Steffen Rendle, Manuel Stritt, Lars Schmidt-Thieme (2006): Ideas and Improvements for Semantic Wikis Workshop: Semantic Web Personalization, 3rd European Semantic Web Conference (ESWC2006), Budva, Montenegro.
    9. Tue. 23.01 (M) Ontology Recommender Systems. Speaker: Dominik Lubian
      1. [ee] Stuart Middleton, David {De Roure, Nigel Shadbolt (2001): Capturing Knowledge of User Preferences: Ontologies in Recommender Systems Proceedings of the First International Conference on Knowledge Capture, Victoria, British Columbia, Canada.

      2. Further Reading (optionally):
      3. V. Schickel, B. Faltings (2006): Using an Ontologcial A-priori Score to Infer User's Preferences ECAI 2006 Recommender Systems Workshop (in press), Trento, Italy.
    10. Fri. 26.01 (M) Collaborative Filtering. Speaker: Sylvia Voss
      1. B. Sarwar, G. Karypis, J. A. Konstan, J. Riedl (2000): Analysis of Recommendation Algorithms for E-Commerce Proceedings of the 2nd ACM Conference on Electronic Commerce (EC-00), Minneapolis, MN, pp. 158-167.

      2. Further Reading (optionally):
      3. B. Sarwar, G. Karypis, J. A. Konstan, J. Riedl (2001): Item-based collaborative filtering recommendation algorithms WWW '01: Proceedings of the 10th international conference on World Wide Web, pp. 285--295.
      4. 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.
    11. Fri. 26.01 (T) Attack issues in Recommender System. Speaker: Felix Siebenhaar
      1. C. Williams, B. Mobasher, R. Burke, R. Bhaumik, JJ. Sandvig (2006): Detection of Obfuscated Attacks in Collaborative Recommender Systems Proceedings of the ECAI'06 Workshop on Recommender Systems.

      2. Further Reading (optionally):
      3. [ee] Paul-Alexandru Chirita, Wolfgang Nejdl, Cristian Zamfir (2005): Preventing shilling attacks in online recommender systems WIDM '05: Proceedings of the 7th annual ACM international workshop on Web information and data management, ACM Press, pp. 67--74.
      4. [ee] Shyong K. Lam, John Riedl (2004): Shilling recommender systems for fun and profit WWW '04: Proceedings of the 13th international conference on World Wide Web, ACM Press, pp. 393--402.
    12. Tue. 30.01. (M) Collaborative Tagging. Speaker: Franziska Mill
      1. Zhichen Xu, Yun Fu, Jianchang Mao, Difu Su (2006): Towards the Semantic Web: Collaborative Tag Suggestion Collaborative Web Tagging Workshop, WWW 2006, Edinburgh.
      2. [ee] Scott A. Golder , Bernardo A. Huberman (2006): Usage patterns of collaborative tagging systems Journal of Information Science, pp. 198--208.

      3. Further Reading (optionally):
      4. Rick Wash, Emilee Rader (2006): Collaborative Filtering with del.icio.us Conference on Human Factors in Computing Systems, CHI 2006, Montreal, Canada. 2006.
    13. Fri. 02.02. (T) Interactive Recommender Systems. Speaker: Benedikt Nienhaus
      1. Barry Smyth, Lorraine McGinty, James Reilly, Kevin McCarthy (2004): Compound Critiques for Conversational Recommender Systems Proceedings of Web Intelligence 2004, pp. 145--151.

      2. Further Reading (optionally):
      3. F. Ricci, T. Mahmood (2006): Learning and Adaptivity in Interactive Recommender Proceedings of the ECAI 2006 Workshop on Recommender Systems.
      4. C. A. Thompson, M. Göker, P. Langley (2004): A personalized system for conversational recommendations Journal of Artificial Intelligence Research, 21, pp. 393--428.
    14. Fri. 02.02 (M) Trust-Aware RS. Speaker: Dennis Holzberg
      1. P. Massa, P. Avesani (2006): Trust-aware Bootstrapping of Recommender Systems Proceedings of the ECAI'06 Workshop on Recommender Systems.

      2. Further Reading (optionally):
      3. J. L. de la Rosa, M. Montaner, J. M. Lopez (2006): Opinion Based Filtering Proceedings of the ECAI 2006 Workshop on Recommender Systems.
      4. [ee] P. Massa, P. Avesani (2004): Trust-aware collaborative filtering for recommender systems Proceedings of Federated Int. Conference On The Move to Meaningful Internet: CoopIS, DOA, ODBASE.
    15. Tue. 06.02 (M) Multi-agent models. Speaker: Katrin Schill
      1. F. Lorenzi, Daniela S. Santosn, Ana Lucia C. Bazzan (2005): Negotiation for task allocation among agents in case-base recommender systems: a swarm-intelligence approach Proceedings of the Workshop Multi-Agent Information Retrieval and Recommender Systems - Nineteenth International Conference on Artificial Intelligence (IJCAI 2005), pp. 23--27.

      2. Further Reading (optionally):
      3. F. Lorenzi, A. L.C. Bazzan, M. Abel (2006): An Architecture for a Multiagent Recommender System in Travel Recommendation Scenarios Proceedings of the ECAI'06 Workshop on Recommender Systems.
      4. Timothy A. Musgrove, Robin H. Walsh (2005): Utilizing multiple agents in dynamic product recommendations Proceedings of the Workshop Multi-Agent Information Retrieval and Recommender Systems - Nineteenth International Conference on Artificial Intelligence (IJCAI 2005).
      5. Yolanda Blanco-Fernandez, Jose J. Pazos-Arias, Alberto Gil-Solla , Manuel Ramos-Cabrer, Belen Barragans-Martinez, Martin Lopez-Nores (2004): Utilizing multiple agents in dynamic product recommendations A Multi-Agent Open Architecture for a TV Recommender System: A Case Study using a Bayesian Strategy. ISMSE '04: Proceedings of the IEEE Sixth International Symposium on Multimedia Software Engineering (ISMSE'04).
    16. ----- (M) Content-based filtering and Hybrid filtering Models. Speaker: Bastian Fiebig
      1. [ee] Robin Burke (1999): The Wasabi Personal Shopper: A Case-Based Recommender System Proceedings of the Sixteenth National Conference on Artificial Intelligence and Eleventh Conference on Innovative Applications of Artificial Intelligence, July 18-22, 1999, Orlando, Florida, USA, AAAI Press / The MIT Press, pp. 844-849.

      2. Further Reading (optionally):
      3. Prem Melville, Raymod Mooney, Ramadass Nagarajan (2002): Content-boosted Collaborative Filtering for Improved Recommendations Eighteenth National Conference on Artificial Intelligence, American Association for Artificial Intelligence, Edmonton, Canada, pp. 187-192.
      4. [ee] Jun Wang, Arjen P. de Vries, Marcel J. T. Reinders (2006): Unifying user-based and item-based collaborative filtering approaches by similarity fusion SIGIR '06: Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval, ACM Press, pp. 501--508.