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Mobile devices equipped with positioning capabilities (e.g., GPS) can ask location-dependent queries to Location Based Services (<i>LBS</i>). To protect privacy, the user location must not be disclosed. Existing solutions utilize a trusted anonymizer between the users and the LBS. This approach has several drawbacks: (<i>i</i>) All users must trust the(More)
In this paper, we present an efficient B +-tree based indexing method, called iDistance, for K-nearest neighbor (KNN) search in a high-dimensional metric space. iDistance partitions the data based on a space-or data-partitioning strategy, and selects a reference point for each partition. The data points in each partition are transformed into a single(More)
In this paper, we present the design and evaluation of PeerDB, a peer-to-peer (P2P) distributed data sharing system. PeerDB distinguishes itself from existing P2P systems in several ways. First, it is a full-fledge data management system that supports fine-grain content-based searching. Second, it facilitates sharing of data without shared schema. Third, it(More)
In this paper, we study the evaluation of skyline queries with partially-ordered attributes. Because such attributes lack a total ordering, traditional index-based evaluation algorithms (e.g., NN and BBS) that are designed for totally-ordered attributes can no longer prune the space as effectively. Our solution is to transform each partially-ordered(More)
In data publishing, the owner delegates the role of satisfying user queries to a third-party publisher. As the publisher may be untrusted or susceptible to attacks, it could produce incorrect query results. In this paper, we introduce a scheme for users to verify that their query results are complete (i.e., no qualifying tuples are omitted) and authentic(More)
In this paper, we propose a novel algorithm to discover the top-k covering rule groups for each row of gene expression profiles. Several experiments on real bioinformatics datasets show that the new top-k covering rule mining algorithm is orders of magnitude faster than previous association rule mining algorithms.Furthermore, we propose a new classification(More)
Given a <i>d</i>-dimensional data set, a point <i>p</i> dominates another point <i>q</i> if it is better than or equal to <i>q</i> in all dimensions and better than <i>q</i> in at least one dimension. A point is a skyline point if there does not exists any point that can dominate it. Skyline queries, which return skyline points, are useful in many decision(More)