Junqiang Liu

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In this paper, we present a novel algorithm Opportune Project for mining complete set of frequent item sets by projecting databases to grow a frequent item set tree. Our algorithm is fundamentally different from those proposed in the past in that it opportunistically chooses between two different structures, array-based or tree-based, to represent projected(More)
In this paper, we propose an efficient algorithm, called TD-FPGrowth (the shorthand for Top-Down FP-Growth), to mine frequent patterns. TD-FP-Growth searches the FP-tree in the top-down order, as opposed to the bottom-up order of previously proposed FP-Growth. The advantage of the topdown search is not generating conditional pattern bases and sub-FP-trees,(More)
Utility mining emerged recently to address the limitation of frequent itemset mining by introducing interestingness measures that reflect both the statistical significance and the user's expectation. Among utility mining problems, utility mining with the itemset share framework is a hard one as no anti-monotone property holds with the interestingness(More)
Medical systems allow patients to receive care at different hospitals. However, this entails considerable inconvenience through the need to transport patients and their medical records between hospitals. The development of Telecare Medicine Information Systems (TMIS) makes it easier for patients to seek medical treatment and to store and access medical(More)
Publishing person specific data while protecting privacy is an important problem. Existing algorithms that enforce the privacy principle called l-diversity are heuristic based due to the NP-hardness. Several questions remain open: can we get a significant gain in the data utility from an optimal solution compared to heuristic ones; can we improve the(More)
The sequence data in real-life application exhibits logical semantic information among their items. However, traditional database techniques were not designed for both sequence data and semantic information and they are incapable of supporting analysis of sequence data with semantic information. In this paper, we present the design, implementation, and(More)
Utility mining is a new development of data mining technology. Among utility mining problems, utility mining with the itemset share framework is a hard one as no anti-monotonicity property holds with the interestingness measure. Prior works on this problem all employ a two-phase, candidate generation approach with one exception that is however inefficient(More)
Separation membranes with high performance can potentially be made by incorporating zeolites (or other nanoporous molecular sieves) in polymeric materials. However, the fabrication of technologically viable membranes has been hampered by poor adhesion between the inorganic crystals and the polymer and by inadequate dispersion of the inorganic particles. We(More)