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A database design methodology is defined for the design of large relational databases. First, the data requirements are conceptualized using an extended entity-relationship model, with the extensions being additional semantics such as ternary relationships, optional relationships, and the generalization abstraction. The extended entity-relationship model is(More)
Methods for efficient mining of frequent patterns have been studied extensively by many researchers. However, the previously proposed methods still encounter some performance bottlenecks when mining databases with different data characteristics, such as dense vs. sparse, long vs. short patterns, memory-based vs. disk-based, etc. In this study, we propose a(More)
Previous studies have shown mining closed patterns provides more benefits than mining the complete set of frequent patterns, since closed pattern mining leads to more compact results and more efficient algorithms. It is quite useful in a data stream environment where memory and computation power are major concerns. This paper studies the problem of mining(More)
With the wide applications of large scale graph data such as social networks, the problem of finding the top-<i>k</i> shortest paths attracts increasing attention. This paper focuses on the discovery of the top-<i>k</i> simple shortest paths (paths without loops). The well known algorithm for this problem is due to Yen, and the provided worstcase bound(More)
Sparse data are becoming increasingly common and available in many real-life applications. However, relatively little attention has been paid to effectively model the sparse data and existing approaches such as the conventional "horizontal¿ and "vertical¿ representations fail to provide satisfactory performance for both storage and query processing, as such(More)