SnoopyDB: narrowing the gap between structured and unstructured information using recommendations

Abstract

Knowledge is structured - until it is stored to a wiki-like information system. In this paper we present the multi-user system SnoopyDB, which preserves the structure of knowledge without restricting the type or schema of inserted information. A self-learning schema system and recommendation engine support the user during the process of inserting information. These dynamically calculated recommendations develop an implicit schema, which is used by the majority of stored information. Further recommendation measures enhance the content both semantically and syntactically and motivate the user to insert more information than he intended to.