Lixin Fu

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Being able to efficiently answer arbitrary OLAP queries that aggregate along any combination of dimensions over numerical and categorical attributes has been a continued, major concern in data warehousing. In this paper, we introduce a new data structure, called Statistics Tree (ST), together with an efficient algorithm called CubiST, for evaluating ad-hoc(More)
Existing decision tree algorithms need to recursively partition dataset into subsets according to some splitting criteria. For large data sets, this requires multiple passes of original dataset and therefore is often infeasible in many applications. In this article we use statistics trees to compute the data cube and then build a decision tree on top of it.(More)
We present a novel approach to speeding up the evaluation of OLAP queries that return aggregates over dimensions containing hierarchies. Our approach is based on our previous version of CubiST (Cubing with Statistics Trees), which pre-computes and stores all possible aggregate views in the leaves of a statistics tree during a one-time scan of the data.(More)
We report on a new, efficient encoding for the data cube, which results in a drastic speed-up of OLAP queries that aggregate along any combination of dimensions over numerical and categorical attributes. We are focusing on a class of queries called cube queries, which return aggregated values rather than sets of tuples. Our approach, termed CubiST ++(More)
Privacy-Preserving Data Mining (PPDM) refers to data mining techniques developed to protect sensitive data while allowing useful information to be discovered from the data. In this chapter the review PPDM and present a broad survey of related issues, techniques, measures, applications, and regulation guidelines. The authors observe that the rapid pace of(More)
Computing data cubes requires the aggregation of measures over arbitrary combinations of dimensions in a data set. Efficient data cube evaluation remains challenging because of the potentially very large sizes of input datasets (e.g., in the data warehousing context), the well-known curse of dimensionality, and the complexity of queries that need to be(More)
Using Internet-enabled mobile handheld devices to access the World Wide Web is a promising addition to the Web and traditional e-commerce. Mobile handheld devices provide convenience and portable access to the huge information on the Internet for mobile users from anywhere and at anytime. However, mobile commerce has not enjoyed the same level of success as(More)
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