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Discovering Image Semantics from Web Pages Using a Text Mining Approach
- Source :
- Advances in Web-Age Information Management ISBN: 9783540407157, WAIM
- Publication Year :
- 2003
- Publisher :
- Springer Berlin Heidelberg, 2003.
-
Abstract
- Traditional content-based image retrieval (CBIR) systems often fail to fulfill a user’s need due to the ‘semantic gap’ existed between the extracted features of the systems and the user’s query. In this paper we propose a novel approach to bridge the semantic gap which is the major deficiency of CBIR systems. We conquer the deficiency by extracting semantics of an image from the environmental texts around it. We apply a text mining process, which adopts the self-organizing map (SOM) learning algorithm as a kernel, on the environmental texts of an image to extract the semantic information from this image. Some implicit semantic information of the images can be discovered after the text mining process. We also define a semantic relevance measure to achieve the semantic-based image retrieval task. We performed experiments on a set of images which are collected from web pages and obtained promising results.
- Subjects :
- Information retrieval
Computer science
business.industry
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Social Semantic Web
Text mining
Semantic grid
Semantic similarity
Semantic computing
Web page
Semantic analytics
Semantic technology
Semantic integration
Case-based reasoning
Semantic Web Stack
business
Image retrieval
Semantic compression
Semantic gap
Subjects
Details
- ISBN :
- 978-3-540-40715-7
- ISBNs :
- 9783540407157
- Database :
- OpenAIRE
- Journal :
- Advances in Web-Age Information Management ISBN: 9783540407157, WAIM
- Accession number :
- edsair.doi...........b6b493cc2bda6c3bf5f8159d17daa5d2