Modeling Users’ Curiosity in Recommender Systems
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- Modeling Users’ Curiosity in Recommender Systems
Recommendations
Acquiring User Information Needs for Recommender Systems
WI-IAT '13: Proceedings of the 2013 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT) - Volume 03Most recommender systems attempt to use collaborative filtering, content-based filtering or hybrid approach to recommend items to new users. Collaborative filtering recommends items to new users based on their similar neighbours, and content-based ...
How do item features and user characteristics affect users’ perceptions of recommendation serendipity? A cross-domain analysis
AbstractSerendipity is one of beyond-accuracy objectives for recommender systems (RSs), which aims to achieve both relevance and unexpectedness of recommendations, so as to potentially address the “filter bubble” issue of traditional accuracy-oriented ...
Modelling trust networks using resistive circuits for trust-aware recommender systems
Recommender systems have been widely used for predicting unknown ratings. Collaborative filtering as a recommendation technique uses known ratings for predicting user preferences in the item selection. However, current collaborative filtering methods ...
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Association for Computing Machinery
New York, NY, United States
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