Jenny Chiang

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In this paper, we employ a novel approach to metarule-guided, multi-dimensional association rule mining which explores a data cube structure. We propose algorithms for metarule-guided mining: given a metarule containing p predicates, we compare mining on an n-dimensional (n-D) cube structure (where p < n) with mining on smaller multiple pdimensional cubes.(More)
A data mining system, DBMiner, has been developed for interactive mining of multiple-level knowledge in large relational databases. The system implements a wide spectrum of data mining functions, including generalization, characterization, association, classi cation, and prediction. By incorporating several interesting data mining techniques, including(More)
A data mining system, DBMiner, has been developed for interactive mining of multiple-level knowledge in large relational databases and data warehouses. The system implements a wide spectrum of data mining functions, including characterization, comparison, association, classi cation, prediction, and clustering. By incorporating several interesting data(More)
Metarule-guided mining is an interactive approach to data mining, where users probe the data under analysis by specifying hypotheses in the form of metarules, or pattern templates. Previous methods for metarule-guided mining of association rules have primarily used a transac-tion/relation table-based structure. Such approaches require costly, multiple scans(More)
Multimedia data mining is the mining of high-level multimedia information and knowledge from large multimedia databases. A multimedia data mining system prototype, MultiMediaMiner, has been designed and developed. It includes the construction of a multimedia data cube which facilitates multiple dimensional analysis of multimedia data, primarily based on(More)
Based on our years-of-research, a data mining system, DB-Miner, has been developed for interactive mining of multiple-level knowledge in large relational databases. The system implements a wide spectrum of data mining functions, including generalization, characterization, association, classification, and prediction. By incorporation of several interesting(More)
For many applications such as accounting, banking, business transaction processing systems, geographical information systems, medical record book keeping, etc., the changes made on their databases over time are a valuable source of information which can direct the future operation of the enterprise. In this thesis, we will focus on relational databases with(More)
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