Workshop on Case Based Reasoning and Personalization 6 th European Conference on Case Based Reasoning ECCBR 2002 September 4 th , 2002 Aberdeen , Scotland Position Papers

The importance of user context as a means of delivering personalised and context-sensitive systems is discussed. Relevant aspects of personalisation and context technology are covered. The intention is to inspire those interested in Case-base reasoning and personalisation from background and experience in other disciplines such as information retrieval, adaptive user interfaces, user modelling and mobile computing. Descriptions of personalisation and context are followed by their use in information retrieval and their importance and use in ambient computing. Relevant literature that may be a motivating source for interested readers are provided. Various questions are also raised in initiating discussion on this topic.

[1]  Derek Bridge,et al.  Product Recommendation Systems: A New Direction , 2001 .

[2]  David Leake,et al.  Capture, Storage and Reuse of Lessons about Information Resources: Supporting Task-Based Information Search* , 2000 .

[3]  Pádraig Cunningham,et al.  An on-line evaluation framework for recommender systems , 2002 .

[4]  John Yen,et al.  Introduction , 2004, CACM.

[5]  Paolo Avesani,et al.  Collaborative Case-Based Recommender Systems , 2002, ECCBR.

[6]  Ulrike Gretzel,et al.  Behavioral Foundations for Human-Centric Travel Decision-Aid Systems , 2002, ENTER.

[7]  Parke Godfrey,et al.  An overview of cooperative answering , 1992, Journal of Intelligent Information Systems.

[8]  Cynthia A. Thompson,et al.  Personalized Conversational Case-Based Recommendation , 2000, EWCBR.

[9]  Ana Gabriela Maguitman,et al.  Assessing Conceptual Similarity to Support Concept Mapping , 2002, FLAIRS Conference.

[10]  D. Fesenmaier,et al.  Assessing structure in the pleasure trip planning process. , 2000 .

[11]  Kristian J. Hammond,et al.  The FindMe Approach to Assisted Browsing , 1997, IEEE Expert.

[12]  David C. Wilson,et al.  A Case-Based Framework for Interactive Capture and Reuse of Design Knowledge , 2001, Applied Intelligence.

[13]  Joan Feigenbaum,et al.  The Role of Trust Management in Distributed Systems Security , 2001, Secure Internet Programming.

[14]  Ryan Scherle,et al.  Towards context-based search engine selection , 2001, IUI '01.

[15]  Barry Smyth,et al.  Comparison-Based Recommendation , 2002, ECCBR.

[16]  David B. Leake,et al.  WordSieve: A Method for Real-Time Context Extraction , 2001, CONTEXT.

[17]  Michael M. Richter,et al.  The Knowledge Contained in Similarity Measures , 1995 .

[18]  Angelo Susi,et al.  Collaborative Radio Community , 2002, AH.

[19]  Robin Burke,et al.  Knowledge-based recommender systems , 2000 .

[20]  Pip Forer,et al.  Information Technology and Tourism: A Challenging Relationship , 2002 .

[21]  John F. Canny,et al.  Collaborative filtering with privacy , 2002, Proceedings 2002 IEEE Symposium on Security and Privacy.

[22]  Markus A. Thies Adaptive User Interfaces , 1994, IFIP Congress.

[23]  Francesco Ricci,et al.  ITR: A Case-Based Travel Advisory System , 2002, ECCBR.

[24]  David Leake,et al.  Goal-Based Explanation Evaluation , 1991, Cogn. Sci..

[25]  Kristian J. Hammond,et al.  Knowledge-Based Navigation of Complex Information Spaces , 1996, AAAI/IAAI, Vol. 1.

[26]  Joaquin Delgado,et al.  Knowledge Bases and User Profiling in Travel and Hospitality Recommender Systems , 2002, ENTER.

[27]  Barry Smyth,et al.  Delivering Personalized Information: What You Get Is What You Want , 2001, Künstliche Intell..

[28]  Joseph A. Konstan,et al.  Research resources for recommender systems , 1999 .