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As a robust similarity measurement, Earth Mover's Distance (EMD) has been widely adopted in many real-world applications, such as machine learning, computer vision and natural language processing. In this paper, we study the problem of EMD-based similarity search, which aims at finding all histogram objects from a dataset whose EMD is within a pre-defined threshold from the given query. Since the time complexity of computing EMD is rather high, it is essential to devise effective techniques to accelerate the query processing. To this end, we propose a filter-and-verification framework: In the filter step, we devise three effective strategies to prune dissimilar objects in batch by sharing the computation between multiple objects. In the verification step, we develop novel flow adjustment techniques to incrementally calculate the EMD of candidates and enable early termination. We justify our proposed framework by conducting both theoretical analysis and extensive experiments. The results on four real world datasets show that our proposed techniques achieve up to an order of magnitude performance gain than state-of-the-art approaches.

In this paper, the authors propose a new electronic commerce architecture in the cloud that satisfies the requirements of the cloud. This architecture includes five technologies, which are the massive EC data storage technology in the cloud, the massive EC data processing technology in the cloud, the EC security management technology in the cloud, OLAP technology for EC in the cloud, and active EC technology in the cloud. Finally, a detailed discussion of future trends for EC in the cloud environment is presented in this paper.

This paper presents a Chu spaces semantics of typical control flow of WS-BPEL including fault handling and link semantics. BPEL-CF is proposed as a simplification of this subset of WS-BPEL. For the compositional modeling of BPEL, the authors present a Chu spaces process algebra. This algebra allows faults to be thrown at any point of execution and take link-based synchronization into consideration. The paper gives the abstract syntax of BPEL-CF, the semantic algebra, and the valuation functions for computing the Chu spaces denotations of BPEL-CF programs.

Abstract: Personalized service systems are an effective way to help users obtain recommendations for unseen items, within the enormous volume of information available based on their preferences. The most commonly used personalized service system methods are collaborative filtering, content-based filtering, and hybrid filtering. Unfortunately, each method has its drawbacks. This paper proposes a new method which unified partition-based collaborative filtering and meta-information filtering. In partition-based collaborative filtering the user-item rating matrix can be partitioned into low-dimensional dense matrices using a matrix clustering algorithm. Recommendations are generated based on these low-dimensional matrices. Additionally, the very low ratings problem can be solved using meta-information filtering. The unified method is applied to a digital resource management system. The experimental results show the high efficiency and good performance of the new approach. [Copyright &y& Elsevier]