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D. McSherry (2002)
Mixed-Initiative Dialogue in Case-Based Reasoning
D. McSherry (2003)
Increasing Dialogue Efficiency in Case-Based Reasoning Without Loss of Solution Quality
R. Burke (2002)
Interactive Critiquing forCatalog Navigation in E-CommerceArtificial Intelligence Review, 18
D. McSherry (2004)
Advances in Case-Based Reasoning
D. McSherry (2003b)
Case-Based Reasoning Research and Development
D. McSherry (2004)
Incremental Relaxation of Unsuccessful Queries
D. McSherry (2001)
Minimizing Dialog Length in Interactive Case-Based Reasoning
Frode Sørmo, J. Cassens, A. Aamodt (2005)
Explanation in Case-Based Reasoning–Perspectives and GoalsArtificial Intelligence Review, 24
D. McSherry (2002)
Recommendation Engineering
James Reilly, Kevin McCarthy, L. McGinty, Barry Smyth (2005)
Explaining Compound CritiquesArtificial Intelligence Review, 24
D. McSherry (2002)
The inseparability problem in interactive case-based reasoningKnowl. Based Syst., 15
K. Evans-Romaine, C. Marling (2003)
Prescribing ex-ercise regimens for cardiac and pulmonary disease patients with cbr
Andreas Kohlmaier, Sascha Schmitt, R. Bergmann (2001)
A Similarity-Based Approach to Attribute Selection in User-Adaptive Sales Dialogs
D. Aha, Len Breslow, Hector Muñoz-Avila (2001)
Conversational Case-Based ReasoningApplied Intelligence, 14
H. Shimazu (2002)
ExpertClerk: A Conversational Case-Based Reasoning Tool forDeveloping Salesclerk Agents in E-Commerce WebshopsArtificial Intelligence Review, 18
Michelle Doyle, P. Cunningham (2000)
A Dynamic Approach to Reducing Dialog in On-Line Decision Guides
L. McGinty, Barry Smyth (2002)
Comparison-Based Recommendation
Jonathan Herlocker, J. Konstan, J. Riedl (2000)
Explaining collaborative filtering recommendations
K. Hammond, R. Burke, K. Schmitt (1994)
A Case-Based Approach to Knowledge Navigation
E. Armengol, A. Palaudàries, E. Plaza (2001)
Individual Prognosis of Diabetes Long-term Risks: A CBR ApproachMethods of Information in Medicine, 40
D. McSherry (2003)
Similarity and Compromise
J. Kassirer, R. Kopelman (1991)
Learning Clinical Reasoning
F. Sørmo, A. Aamodt (2002)
Proceedings of the ECCBR-02 Workshop on Case-Based Reasoning for Education and Training
Frode Sørmo, A. Aamodt (2002)
Knowledge communication and CBR
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Medical Problem Solving: An Analysis of Clinical ReasoningBulletin of the New York Academy of Medicine, 55
D. McSherry (2001)
Interactive Case-Based Reasoning in Sequential DiagnosisApplied Intelligence, 14
D. McSherry (1999)
Strategic induction of decision treesKnowl. Based Syst., 12
K.J. Hammond, R. Burke, K. Schmitt (1996)
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T. Gaasterland, P. Godfrey, J. Minker (1992)
An overview of cooperative answeringJournal of Intelligent Information Systems, 1
There is increasing awareness in recommender systems research of the need to make the recommendation process more transparent to users. Following a brief review of existing approaches to explanation in recommender systems, we focus in this paper on a case-based reasoning (CBR) approach to product recommendation that offers important benefits in terms of the ease with which the recommendation process can be explained and the system’s recommendations can be justified. For example, recommendations based on incomplete queries can be justified on the grounds that the user’s preferences with respect to attributes not mentioned in her query cannot affect the outcome. We also show how the relevance of any question the user is asked can be explained in terms of its ability to discriminate between competing cases, thus giving users a unique insight into the recommendation process.
Artificial Intelligence Review – Springer Journals
Published: Mar 29, 2005
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