Automatic selection of attributes by importance in relevance feedback visualisation
UNSPECIFIED (2004) Automatic selection of attributes by importance in relevance feedback visualisation. In: 8th International Conference on Information Visualisation, JUL 14-16, 2004, London, ENGLAND.Full text not available from this repository.
Relevance feedback visualisation (RFV) is a technique developed to visualise the feature values of returned results in a content-based image retrieval system that incorporates relevance feedback. RFV is used also to re-sort retrieved results according to user requirements, enable the interactive investigation of pertinent features and permit the discovery of otherwise unidentifiable trends in the dataset. When large numbers of features are involved, manually determining which feature attribute graphs are the most important can be a burdensome task. In this paper, a method for automatically sorting attribute graphs according to their significance in the search operation is introduced. The result is that features worthy of further investigation are immediately identified, the user interface is improved, and the CBIR system is made more effective.
|Item Type:||Conference Item (UNSPECIFIED)|
|Subjects:||Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software|
|Series Name:||IEEE CONFERENCE ON INFORMATION VISUALIZATION - PROCEEDINGS|
|Journal or Publication Title:||EIGHTH INTERNATIONAL CONFERENCE ON INFORMATION VISUALISATION, PROCEEDINGS|
|Publisher:||IEEE COMPUTER SOC|
|Editor:||Banissi, E and Borner, K and Chen, C and Dastbaz, M and Clapworthy, G and Faiola, A and Izquierdo, E and Maple, C and Roberts, J and Moore, C and Ursyn, A and Zhang, JJ|
|Number of Pages:||8|
|Page Range:||pp. 588-595|
|Title of Event:||8th International Conference on Information Visualisation|
|Location of Event:||London, ENGLAND|
|Date(s) of Event:||JUL 14-16, 2004|
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