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Ben Kao
Researcher at University of Hong Kong
Publications - 159
Citations - 6959
Ben Kao is an academic researcher from University of Hong Kong. The author has contributed to research in topics: Uncertain data & Set (abstract data type). The author has an hindex of 42, co-authored 150 publications receiving 6399 citations. Previous affiliations of Ben Kao include Stanford University & Princeton University.
Papers
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Proceedings ArticleDOI
Secure kNN computation on encrypted databases
TL;DR: A new asymmetric scalar-product-preserving encryption (ASPE) that preserves a special type of scalar product and is shown to resist practical attacks of a different background knowledge level, at a different overhead cost.
Proceedings ArticleDOI
A General Incremental Technique for Maintaining Discovered Association Rules
TL;DR: The study shows that the new incremental algorithm is signijcantly faster than the traditional approach of mining the whole updated database, and compared with the best algorithms for mining association rules studied so far.
Book ChapterDOI
Mining frequent itemsets from uncertain data
TL;DR: Through extensive experiments, it is shown that the data trimming technique can achieve significant savings in both CPU cost and I/O cost.
Proceedings Article
Indexing multi-dimensional uncertain data with arbitrary probability density functions
TL;DR: The U-tree is proposed, an access method designed to optimize both the I/O and CPU time of range retrieval on multi-dimensional imprecise data and is fully dynamic, and does not place any constraints on the data pdfs.
Proceedings ArticleDOI
Efficient Clustering of Uncertain Data
TL;DR: This work studies various pruning methods to avoid expensive expected distance calculation in the UK-means algorithm, which is based on the traditional K-mean algorithm.