WordNet: a lexical database for English
Communications of the ACM
An Adapted Lesk Algorithm for Word Sense Disambiguation Using WordNet
CICLing '02 Proceedings of the Third International Conference on Computational Linguistics and Intelligent Text Processing
A Flexible Content-based Image Retrieval System with Combined Scene Description Keyword
ICMCS '96 Proceedings of the 1996 International Conference on Multimedia Computing and Systems
Extended gloss overlaps as a measure of semantic relatedness
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
A Study on Effective Tactile Feeling of Control Panels for Electrical Appliances
Proceedings of the 13th International Conference on Human-Computer Interaction. Part II: Novel Interaction Methods and Techniques
How to design Kansei retrieval systems?
WAIM'10 Proceedings of the 11th international conference on Web-age information management
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Nowadays, the processing of KANSEI information is very important in intelligent computing field. Particularly, it is very interesting in image retrieval to deal with human's KANSEI. In this paper, we use natural language for the representation of KANSEI, including the image structure of Human's idea, which we can not observe. And then, a KANSEI-Adjective is used as a natural language querying method: In other words, this paper presents the image retrieval based on KANSEI. We propose the background image retrieval based on KAC (KANSEI-Adjective of Color) to represent the sensibility of color. Our method for processing of KANSEI information is the measure of similarity by using the adaptive Lesk algorithm in WordNet. In our experimental results, we are able to retrieve background images with the most appropriate color in term of the query's feeling. Furthermore, the method achieves an average rate of 63% user's satisfaction.