Research on Distributed and Evolutional Database Systems

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The aim of this research is to develop new database system technologies with dynamic reorganization capabilities, which integrate a variety of types of data on networks, and allow the evolution of each data structure. The following are the major results of the research project :(1) Organization of multimedia dataConsidering the major characteristic of video/image data (data continuity), we developed an algebraic video retrieval model, video authoring systems by graph-theoretical approach and AI approach (story grammer), a copyright protection and a charge management system by content capsulation, a new data access control method for multimedia data with continuous levels of details, an extracting and indexing method by speech/image/character recognition technologies, an automatic classification method for sport video scenes.(2) Internet database technologiesWe developed an automatic classification method of Web data by the Self-organizing map, an information filtering method by the dynamic decision tree, a consistency control method for hyperlinks by the path existence constrainta, and a retrieval engine for Web data by association rules of data mining technologies.(3) Mobile and portable databasesWe developed a mobile database system by the active database mechanism in order to cope with several problems in mobile communication. Furthermore, we developed an efficient query processing method by using location information and data replica.(4) Distributed agent databasesIn order to integrate heterogeneous information resources (e. g. semistructured and multimedia data) in open networks, we developed mediation systems by the agent technology (KQML), the distributed object management technologies (CORBA), the ECA rule technology, and the deductive and object-oriented technology.