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Well-Argued Recommendation: Adaptive Models Based on Words in Recommender Systems
Abstract : Recommendation systems (RS) take advan- tage of products and users information in order to propose items to consumers. Collaborative, content-based and a few hybrid RS have been developed in the past. In contrast, we propose a new domain-independent semantic RS. By providing textually well-argued recommenda- tions, we aim to give more responsibility to the end user in his decision. The system includes a new similarity measure keeping up both the accuracy of rating predictions and coverage. We propose an innovative way to apply a fast adaptation scheme at a semantic level, provid- ing recommendations and arguments in phase with the very recent past. We have performed several experiments on films data, providing textually well-argued recommendations.
Cited literature [10 references]
https://hal.inria.fr/hal-00916241
Contributor : Eitan Altman <>
Submitted on : Monday, December 9, 2013 - 10:14:07 PM
Last modification on : Tuesday, January 14, 2020 - 11:10:03 AM
Document(s) archivé(s) le : Thursday, March 20, 2014 - 2:05:19 PM
Contributor : Eitan Altman <>
Submitted on : Monday, December 9, 2013 - 10:14:07 PM
Last modification on : Tuesday, January 14, 2020 - 11:10:03 AM
Document(s) archivé(s) le : Thursday, March 20, 2014 - 2:05:19 PM
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