Generating transparent, steerable recommendations from textual descriptions of items

We propose a recommendation technique that works by collecting text descriptions of items and using this textual aura to compute the similarity between items using techniques drawn from information retrieval. We show how this representation can be used to explain the similarities between items using terms from the textual aura and further how it can be used to steer the recommender. We describe a system that demonstrates these techniques and we’ll detail some preliminary experiments aimed at evaluating the quality of the recommendations and the effectiveness of the explanations of item similarity. Categories and Subject Descriptors H.3.3 [Information Search And Retrieval]: Information Filtering General Terms Algorithms, Measurement, Performance Keywords Steerable recommender, Explainable recommende

• Type: Conference
• Year: 2009
• Where: RECSYS
• Authors: Stephen J. Green, Paul Lamere, Jeffrey Alexander, François Maillet, Susanna Kirk, Jessica Holt, Jackie Bourque, Xiao-Wen Mak
• Keywords: Control Systems, Keywords Steerable Recommender, RECSYS 2009, Search And Retrieval, Textual Aura