<XML><RECORDS><RECORD><REFERENCE_TYPE>0</REFERENCE_TYPE><REFNUM>7970</REFNUM><AUTHORS><AUTHOR>Urban,J.</AUTHOR><AUTHOR>Jose,J.M.</AUTHOR></AUTHORS><YEAR>2006</YEAR><TITLE>EGO: A Personalised Multimedia Management and Retrieval Tool</TITLE><PLACE_PUBLISHED>International Journal of Intelligent Systems (Special issue on “Intelligent Multimedia Retrieval”), Volume 21, Issue 7</PLACE_PUBLISHED><PUBLISHER>Wiley</PUBLISHER><PAGES>725-745</PAGES><ISBN>0884-8173</ISBN><LABEL>Urban:2006:7970</LABEL><KEYWORDS><KEYWORD>content-based image retrieval</KEYWORD></KEYWORDS<ABSTRACT>The problems of Content-Based Image Retrieval (CBIR) systems can be attributed to the semantic gap between the low-level data representation and the high-level concepts the user associates with images, on the one hand, and the time-varying and often vague nature of the underlying information need, on the other. These problems can be addressed by improving the interaction between the user and the system. In this paper, we sketch the development of CBIR interfaces and introduce our view on how to solve some of the problems these interfaces present. To address the semantic gap and long-term multifaceted information needs, we propose a “retrieval in context” system, EGO. EGO is a tool for the management of image collections, supporting the user through personalisation and adaptation. We will describe how it learns from the user’s personal organisation, allowing it to recommend relevant images to the user. The recommendation algorithm is described, which is based on relevance feedback techniques. Additionally, we provide results of a performance analysis of the recommendation system and of a preliminary user study.</ABSTRACT></RECORD></RECORDS></XML>