期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2012
卷号：40
期号：1
页码：023-028
出版社：Journal of Theoretical and Applied
摘要：Technological and dynamic growths of digital media have increased volume of the multimedia corpus. Due to this growth, it is strongly urged for a system that can efficiently and effectively compiles the user demand, and retrieving the relevant images. Keyword based system retrieves an image on syntactic matching, i.e. string matching not concept. Content Based Image Retrieval (CBIR) systems retrieve the image based on low level features and still exist a gap is called semantic. This paper discussed snippet technique that covers the semantic gap as well as Word Sense disambiguation problems. It extracts user queries for expansion with the help of Knowledgebase WordNet and ConceptNet. Experiments performed on the open benchmark image dataset LabelMe. A substantial improvement has been achieved in terms of precision and recall. Remarkably outperformed of Results and showed 84% corrects.
