<XML><RECORDS><RECORD><REFERENCE_TYPE>3</REFERENCE_TYPE><REFNUM>9190</REFNUM><AUTHORS><AUTHOR>Leelanupab,T.</AUTHOR><AUTHOR>Feng,Y.</AUTHOR><AUTHOR>Stathopoulos,V.</AUTHOR><AUTHOR>Jose,J.M.</AUTHOR></AUTHORS><YEAR>2009</YEAR><TITLE>A Simulated Evaluation of Image Browsing Using High-Level Classi cation</TITLE><PLACE_PUBLISHED>4th International Conference on Semantic and Digital Media Technologies, SAMT 2009</PLACE_PUBLISHED><PUBLISHER>N/A</PUBLISHER><LABEL>Leelanupab:2009:9190</LABEL><ABSTRACT>In this paper, we present a study of adaptive image browsing,based on high-level classification. The underlying hypothesis is that the performance of a browsing model can be improved by integrating high-level semantic concepts. We introduce a multi-label classification model designed to alleviate a multi-class problem in image classi cation. The effectiveness of this approach is evaluated by using a simulated user evaluation methodology. The results show that the classification assists users to narrow down the search domain and to retrieve more relevant results with respect to less amount of browsing effort.</ABSTRACT></RECORD></RECORDS></XML>