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Replica value determination plays an important role in the problem of replication in data grid, since only replicating high value replicas can improve the replication efficiency. However, replica value determination methods applied now do not perform well, because they cannot well adapt to the changes of file access patterns. We address this problem by(More)
Web service recommendation has become a hot yet fundamental research topic in service computing. The most popular technique is the Collaborative Filtering (CF) based on a user-item matrix. However, it cannot well capture the relationship between Web services and providers. To address this issue, we first design a cube model to explicitly describe the(More)
This paper presents an efficient and robust content-based large medical image retrieval method in mobile Cloud computing environment, called the MIRC. The whole query process of theMIRC is composed of three steps. First, when a clinical user submits a query image Iq, a parallel image set reduction process is conducted at a master node. Then the candidate(More)
This paper presents an efficient algorithm called CosMinert for interesting pattern discovery. The widely used cosine similarity, found to possess the null-invariance property and the anti-cross-support-pattern property, is adopted as the interestingness measure in CosMinert . CosMinert is generally an FP-growth-like depth-first traversal algorithm that(More)
Shilling attackers apply biased rating profiles to recommender systems for manipulating online product recommendations. Although many studies have been devoted to shilling attack detection, few of them can handle the <i>hybrid</i> shilling attacks that usually happen in practice, and the studies for real-life applications are rarely seen. Moreover, little(More)
Information-theoretic clustering aims to exploit information-theoretic measures as the clustering criteria. A common practice on this topic is the so-called Info-Kmeans, which performs K-means clustering with KL-divergence as the proximity function. While expert efforts on Info-Kmeans have shown promising results, a remaining challenge is to deal with(More)
Multi-relational networks are ubiquitous in many fields such as bibliography, twitter, and healthcare. There have been many studies in the literature targeting at discovering communities from social networks. However, most of them have focused on single-relational networks. A hint of methods detected communities from multi-relational networks by converting(More)