Modeling Multimodal Expression of User's Affective Subjective Experience
User Modeling and User-Adapted Interaction
Mining Multimedia Subjective Feedback
Journal of Intelligent Information Systems
Supporting the Interaction between User and Web-Based Multimedia Information
WI '03 Proceedings of the 2003 IEEE/WIC International Conference on Web Intelligence
Relevance feedback: a power tool for interactive content-based image retrieval
IEEE Transactions on Circuits and Systems for Video Technology
Affective image classification using features inspired by psychology and art theory
Proceedings of the international conference on Multimedia
Emotion based classification of natural images
Proceedings of the 2011 international workshop on DETecting and Exploiting Cultural diversiTy on the social web
Emotion-based textile indexing using colors, texture and patterns
ISVC'06 Proceedings of the Second international conference on Advances in Visual Computing - Volume Part II
User interest and social influence based emotion prediction for individuals
Proceedings of the 21st ACM international conference on Multimedia
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The Kansei (Japanese for sensitivity) Distributed Information Management Environment, or K-DIME, software environment lets users or software applications fetch multimedia material from the Web on the basis of textual keywords and filter it using a Kansei user model (KUM). The KUM learns a mapping between low-level features of the multimedia data and impression words - such as "romantic" - expressed in natural language. K-DIME acts as a metasearch engine for the Web.