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Object-oriented programming is well-suited to such data-intensive application domains as CAD/CAM, AI, and OIS (office information systems) with multimedia documents. At MCC we have built a prototype object-oriented database system, called ORION. It adds persistence and sharability to objects created and manipulated in applications implemented in an(More)
Presented in this paper is the data model for ORION, a prototype database system that adds persistence and sharability to objects created and manipulated in object-oriented applications. The ORION data model consolidates and modifies a number of major concepts found in many object-oriented systems, such as objects, classes, class lattice, methods, and(More)
The performance of object access can be drastically improved by efficient object prefetch. In this paper we present a new object prefetch policy, Selective Eager Object Fetch(SEOF) which prefetches objects only from selected candidate pages without using any high level object semantics. Our policy considers both the correlations and the frequencies of(More)
—The SPY-TEC (Spherical Pyramid-Technique) was proposed as a new indexing method for high-dimensional data spaces using a special partitioning strategy that divides a d-dimensional data space into 2d spherical pyramids. In the SPY-TEC, an efficient algorithm for processing hyperspherical range queries was introduced with a special partitioning strategy.(More)
In this paper, we propose a multi-strategic matching and merging approach to find correspondences between ontologies based on the syntactic or semantic characteristics and constraints of the Topic Maps. Our multi-strategic matching approach consists of a linguistic module and a Topic Map constraints-based module. A linguistic module computes similarities(More)
In this paper, targeting del.icio.us tag data, we propose a method, FolksoViz, for deriving subsumption relationships between tags by using Wikipedia texts, and visualizing a folksonomy. To fulfill this method, we propose a statistical model for deriving subsumption relationships based on the frequency of each tag on the Wikipedia texts, as well as the TSD(More)