Abstract
We explore the use of soft computing and user defined classifications in multimedia database systems for content-based queries. With traditional database systems, objects/tuples are grouped into classes/relations using `hard' membership. Hence, the result of a query to obtain the members of a class is a fixed set. With multimedia databases, however, an object may belong to different classes with different probabilities (`soft' membership). In addition, alternative users may classify objects differently due to subjectivity of human perception on multimedia objects. In order to remedy for this situation, we propose a unified model that captures both conventional techniques and soft memberships. We implemented the model by extending the traditional database query capabilities such that the result of a query depends on the user who submits the query. We compared our proposed system with conventional image retrieval systems and observed a significant margin of improvement in matching the user expectations.