Integrated personal recommender systems

ABSTRACT

Recommender Systems belong to a class of systems intended to assist individuals make evaluations about entities in meaningful ways. In this paper we discuss the issues in the design of integrated recommender systems and suggest a framework that takes the perspective of an individual functioning in multiple domains. This is particularly applicable today with the rapidly increasing diffusion of personalized, networked mobile devices. We present some preliminary design ideas in the form of a functional prototype.

REFERENCES

• 1: Gediminas Adomavicius , Alexander Tuzhilin, Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions, IEEE Transactions on Knowledge and Data Engineering, v.17 n.6, p.734-749, June 2005 [doi>10.1109/TKDE.2005.99]
• 2: Ahmed, M. D. Design and Implementation of Scenario Driven Flexible Decision Support Systems Generator. Masters Thesis, Department of Management Science and Information Systems, University of Auckland, Auckland, New Zealand, 2002.
• 3: Berry, M. J. A. and Linoff, G. Data Mining Techniques, John Wiley & Sons, 1997.
• 4: Burke, R. Knowledge-based Recommender Systems. IEEE Transactions on. Knowledge and Data Engineering., 17, 6 (2000), 734--749.
• 5: Giuseppe Carenini , Jocelyin Smith , David Poole, Towards more conversational and collaborative recommender systems, Proceedings of the 8th international conference on Intelligent user interfaces, January 12-15, 2003, Miami, Florida, USA [doi>10.1145/604045.604052]
• 6: Daniel R. Dolk , Jeffrey E. Kottemann, Model integration and a theory of models, Decision Support Systems, v.9 n.1, p.51-63, Jan. 1993 [doi>10.1016/0167-9236(93)90022-U]
• 7: David Goldberg , David Nichols , Brian M. Oki , Douglas Terry, Using collaborative filtering to weave an information tapestry, Communications of the ACM, v.35 n.12, p.61-70, Dec. 1992 [doi>10.1145/138859.138867]
• 8: González, G., López, B. and Lluís de la Rosa, J. A Multi-Agent Smart User Model for Cross-domain Recommender systems. IUI'05 Workshop: Beyond Personalization 2005, San Diego, USA, 2005.
• 9: Nathaniel Good , J. Ben Schafer , Joseph A. Konstan , Al Borchers , Badrul Sarwar , Jon Herlocker , John Riedl, Combining collaborative filtering with personal agents for better recommendations, Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence, p.439-446, July 18-22, 1999, Orlando, Florida, United States
• 10: Zan Huang , Wingyan Chung , Thian-Huat Ong , Hsinchun Chen, A graph-based recommender system for digital library, Proceedings of the 2nd ACM/IEEE-CS joint conference on Digital libraries, July 14-18, 2002, Portland, Oregon, USA [doi>10.1145/544220.544231]
• 11: Klein, G. A. Automated Aids for the Proficient Decision Maker. Proceedings of the 1980 IEEE Systems, Man and Cybernetics Conference., (1980), 301--304.
• 12: Joseph A. Konstan, Introduction to recommender systems: Algorithms and Evaluation, ACM Transactions on Information Systems (TOIS), v.22 n.1, p.1-4, January 2004 [doi>10.1145/963770.963771]
• 13: George M. Marakas, Decision support systems in the twenty-first century, Prentice-Hall, Inc., Upper Saddle River, NJ, 1998
• 14: Bradley Norman Miller , John T. Riedl , John Vincent Carlis, Toward a personal recommender system, University of Minnesota, 2003
• 15: Mintzberg, H., D. Raisinghani and A. Theoret. The Structure of "Unstructured" Decision Processes. Administrative Science Quarterly., 21 (1976), 246--274.
• 16: Niinivaara, O. Agent-Based Recommender Systems, University of Helsinki, Department of Computer Science., (2004), 1--48.
• 17: John O'Donovan , Barry Smyth, Trust in recommender systems, Proceedings of the 10th international conference on Intelligent user interfaces, January 10-13, 2005, San Diego, California, USA [doi>10.1145/1040830.1040870]
• 18: Al Mamunur Rashid , Istvan Albert , Dan Cosley , Shyong K. Lam , Sean M. McNee , Joseph A. Konstan , John Riedl, Getting to know you: learning new user preferences in recommender systems, Proceedings of the 7th international conference on Intelligent user interfaces, January 13-16, 2002, San Francisco, California, USA [doi>10.1145/502716.502737]
• 19: Paul Resnick , Hal R. Varian, Recommender systems, Communications of the ACM, v.40 n.3, p.56-58, March 1997 [doi>10.1145/245108.245121]
• 20: Rowe, A. J. and Boulgarides, J. D. Managerial Decision Making, Upper Saddle River, NJ: Prentice Hall, 1994.
• 21: J. Ben Schafer , Joseph A. Konstan , John Riedl, E-Commerce Recommendation Applications, Data Mining and Knowledge Discovery, v.5 n.1-2, p.115-153, January-April 2001 [doi>10.1023/A:1009804230409]
• 22: Upendra Shardanand , Pattie Maes, Social information filtering: algorithms for automating “word of mouth”, Proceedings of the SIGCHI conference on Human factors in computing systems, p.210-217, May 07-11, 1995, Denver, Colorado, United States [doi>10.1145/223904.223931]
• 23: Herbert Alexander Simon, The New Science of Management Decision, Prentice Hall PTR, Upper Saddle River, NJ, 1977
• 24: Srikumar, K., Bhasker, B. Personalized Product Selection in Internet Business. Journal of Electronic Commerce Research., 5 (2004), 216--227.
• 25: Van Alstyne, M. and Brynjolfsson, E. Electronic Communities: Global Village or Cyberbalkans? MIT Sloan School., (1997), 1--32.
• 26: Charu C. Aggarwal , Joel L. Wolf , Kun-Lung Wu , Philip S. Yu, 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, p.201-212, August 15-18, 1999, San Diego, California, United States [doi>10.1145/312129.312230]
• 27: Chien-Chih Yu, A web-based consumer-oriented intelligent decision support system for personalized e-services, Proceedings of the 6th international conference on Electronic commerce, October 25-27, 2004, Delft, The Netherlands [doi>10.1145/1052220.1052274]

INDEX TERMS

Primary Classification:
  J. Computer Applications
  J.4 SOCIAL AND BEHAVIORAL SCIENCES

Additional Classification:
  H. Information Systems
  H.4 INFORMATION SYSTEMS APPLICATIONS

General Terms:
Design, Economics, Management

Keywords:
integrated recommender systems, personal decision making