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Title: Re-using Implicit Knowledge in Short-term Information Profiles for Context-sensitive Tasks
Author: Hayes, Conor
Cunningham, Pádraig
Keywords: Computer Science
Issue Date: 22-Feb-2005
Publisher: Trinity College Dublin, Department of Computer Science
Citation: Hayes, Conor; Cunningham, Pádraig. 'Re-using Implicit Knowledge in Short-term Information Profiles for Context-sensitive Tasks'. - Dublin, Trinity College Dublin, Department of Computer Science, TCD-CS-2005-28, 2005, pp15
Series/Report no.: Computer Science Technical Report
Abstract: Typically, case-based recommender systems recommend single items to the on-line customer. In this paper we introduce the idea of recommending a user-defined collection of items where the user has implicitly encoded the relationships between the items. Automated collaborative filtering (ACF), a so-called ‘contentless’ technique, has been widely used as a recommendation strategy for music items. However, its reliance on a global model of the user’s interests makes it unsuited to catering for the user’s local interests. We consider the context-sensitive task of building a compilation, a user-defined collection of music tracks. In our analysis, a collection is a case that captures a specific shortterm information/music need. In an offline evaluation, we demonstrate how a case-completion strategy that uses short-term representations is significantly more effective than the ACF technique. We then consider the problem of recommending a compilation according to the user’s most recent listening preferences. Using a novel on-line evaluation where two algorithms compete for the user’s attention, we demonstrate how a knowledge-light case-based reasoning strategy successfully addresses this problem.
Appears in Collections:Computer Science Technical Reports

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