Cube Based Summaries of Large Association Rule Sets
نویسندگان
چکیده
منابع مشابه
Discovering frequent pattern pairs
Cubes and association rules discover frequent patterns in a data set, most of which are not significant. Thus previous research has introduced search constraints and statistical metrics to discover significant patterns and reduce processing time. We introduce cube pairs (comparing cube groups based on a parametric statistical test) and rule pairs (based on two similar association rules), which ...
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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 of the data in order to nd all the la...
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OF THE DISSERTATION CUBEGRADES – GENERALIZATION OF ASSOCIATION RULES TO MINE LARGE DATASETS by AMIN ARSHAD ABDULGHANI Dissertation Director: Tomasz Imielinski Cubegrades are generalization of association rules which represent how a set of measures (aggregates) is affected by modifying a cube through specialization (rolldown), generalization (rollup) and mutation (which is a change in one of the...
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Similarity assessment is the fundamentally important to various remote sensing applications such as image classification, image retrieval and so on. The objective of similarity assessment is to automatically distinguish differences between images and identify the contents of an image. Unlike the existing feature-based or object-based methods, we concern more about the deep level pattern of imag...
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تاریخ انتشار 2010