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EGO: A personalized multimedia management and retrieval tool
Author(s) -
Urban Jana,
Jose Joemon M.
Publication year - 2006
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.20157
Subject(s) - computer science , personalization , adaptation (eye) , information retrieval , semantic gap , image retrieval , sketch , context (archaeology) , relevance (law) , relevance feedback , representation (politics) , human–computer interaction , world wide web , image (mathematics) , artificial intelligence , paleontology , physics , algorithm , law , political science , optics , biology , politics
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 article, 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 personalization and adaptation. We will describe how it learns from the user's personal organization, 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. © 2006 Wiley Periodicals, Inc. Int J Int Syst 21: 725–745, 2006.