Tasteweights: A visual interactive hybrid recommender system

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Tasteweights: A visual interactive hybrid recommender system is a 2012 conference paper written in English by Bostandjiev S., O'Donovan J., Hollerer T. and published in RecSys'12 - Proceedings of the 6th ACM Conference on Recommender Systems.

[edit] Abstract

This paper presents an interactive hybrid recommendation system that generates item predictions from multiple social and semantic web resources, such as Wikipedia, Facebook, and Twitter. The system employs hybrid techniques from traditional recommender system literature, in addition to a novel interactive interface which serves to explain the recommendation process and elicit preferences from the end user. We present an evaluation that compares different interactive and non-interactive hybrid strategies for computing recommendations across diverse social and semantic web APIs. Results of the study indicate that explanation and interaction with a visual representation of the hybrid system increase user satisfaction and relevance of predicted content. Copyright © 2012 by the Association for Computing Machinery, Inc. (ACM).

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