Unified relevance models for rating prediction in collaborative filtering
ACM Transactions on Information Systems (TOIS)
Affective feedback: an investigation into the role of emotions in the information seeking process
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
Handling data sparsity in collaborative filtering using emotion and semantic based features
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Using emotion to diversify document rankings
ICTIR'11 Proceedings of the Third international conference on Advances in information retrieval theory
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The aim of this poster is to investigate the role of emotion in the collaborative filtering task. For this purpose, a kernel-based collaborative recommendation technique is used. The experiment is conducted on two MovieLens data sets. The emotional features are extracted from the movie reviews and plot summaries. The results show that emotional features are capable of enhancing recommendation effectiveness.