SESAM: searching supported by analysis of metadata

This paper presents a novel approach for database searching where the user is assisted in locating relevant objects in query results. This is made possible by an active user interface which asks the user dynamically generated questions based on collected information of the properties of the objects in the result. The answers to these questions are used to retain only objects with the indicated properties, thereby improving precision. SESAM, a World Wide Web-based prototype based on this approach, is presented. It has been successfully tested using a large, real-life database.

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