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Group-oriented services such as group recommendations aim to provide services for a group of users. For these applications, how to aggregate the preferences of different group members is the toughest yet most important problem. Inspired by game theory, in this paper, we propose to explore the idea of Nash equilibrium to simulate the selections of members in a group by a game process. Along this line,...
With the rapid growth of usage of social network, the patterns, the scales, and the rate of information exchange have brought profound impacts on research and practice in finance. One important topic is the stock market efficiency analysis. Traditional schemes in finance focus on identifying significant abnormal returns triggered by important events. However, those events are merely identified by...
MapReduce (MR) is a popular programming model for the purposes of processing large data sets among data clusters or grids, e.g. a Hadoop environment. Load balancing as a key factor affecting the performance of map resource distribution, has recently gained high concerns to optimize. Current MR processes in the realization of distributing tasks to clusters use hashing with random modulo operations,...
Convolution-based detection models (CDM) have achieved tremendous success in computer vision in last few years, such as deformable part-based models (DPM) and convolutional neural networks (CNN). The simplicity of these models allows for very large scale training to achieve higher robustness and recognition performance. However, the main bottleneck of those powerful state-of-the-art models is the...
The emergence of social networks has provided opportunities for both targeted marketing and viral marketing. By concentrating the efforts on a few key customers, targeted marketing could make the promotion of the items (products) much easier and more cost-effective. On the other hand, viral marketing aims at finding a set of individuals (seeds) to maximize the word-of-mouth propagation of an item...
Recent years have witnessed the increased interests in exploiting influence in social networks for many applications. To the best of our knowledge, from the computational aspect of social influence analysis, most of existing work focus on either describing the influence propagation process or identifying the set of most influential seed nodes. However, these work usually do not distinguish the "independent...
To address the challenge of automated performance benchmarking in virtualized cloud infrastructures, an extensible and adaptable framework called CloudBench has been developed to conduct scalable, controllable, and repeatable experiments in such environments. This paper presents the hardware-in-the-loop simulation technique used in CloudBench, which integrates an efficient discrete-event simulation...
The increasing scale and complexity of virtualized data centers pose significant challenges to system management software stacks, which still rely on special-purpose controllers to optimize the operation of cloud infrastructures. Autonomic computing allows complex systems to assume much of their own management, achieving self-configuration, self-optimization, self-healing, and self-protection without...
Recommender systems suggest a few items from many possible choices to the users by understanding their past behaviors. In these systems, the user behaviors are influenced by the hidden interests of the users. Learning to leverage the information about user interests is often critical for making better recommendations. However, existing collaborative-filtering-based recommender systems are usually...
According to complex conditions in the displaying of atmospheric wind field distribution with VC programming language, implementation method of atmospheric wind field retrieval system detected by lidar based on COM is presented. This method partitioned retrieval system and designed the ports of every modules according to COM criterion and functional requirements of atmospheric wind field retrieval...
This paper presents a computing technique for efficient parallel simulation of large-scale discrete-event models on the IBM Cell Broadband Engine (CBE), which has one Power Processor Element (PPE) and eight Synergistic Processing Elements (SPE). Based on the general-purpose Discrete Event System Specification (DEVS), the technique tackles all performance bottlenecks, combining multi-dimensional parallelism...
We propose a computing technique for efficient parallel simulation of compute-intensive DEVS models on the IBM Cell processor, combining multi-grained parallelism and various optimizations to speed up the event execution. Unlike most existing parallelization strategies, our approach explicitly exploits the massive fine-grained event-level parallelism inherent in the simulation process, while most...
With the development of Web service technology, SOA has so many applications in industries. How to evaluate a domain oriented service becomes an important issue at present. This paper puts forward an extended SOA (exSOA) architecture and a domain expert-based evaluation model for Web service. It evaluates the candidate service by considering the evaluation result from domain expert and the constraint...
The lightweight time warp (LTW) protocol offers a novel approach to high-performance optimistic parallel discrete-event simulation, especially when a large number of simultaneous events need to be executed at each virtual time. With LTW, the local simulation space on each node is partitioned into two sub-domains, allowing purely optimistic simulation to be driven by only a few full-fledged logical...
This paper proposes a novel lightweight time warp (LTW) protocol for high-performance parallel optimistic simulation of large-scale DEVS and cell-DEVS models. By exploiting the characteristics of the simulation process, the protocol is able to set free most logical processes (LPs) from the time warp mechanism, while the overall simulation still executes optimistically, driven by only a few full-fledged...
Query recommendation is a technique that provides better queries to help users to get the needed documents when the original query submitted by the user may be insufficient or imprecise to retrieve those. In this paper a novel method for query recommendation is proposed. It is different from traditional methods in two aspects: (1) it breaks URLs into independent tokens and uses a TF-IQF model to present...
The large-scaled worm infestation promotes the investigation of worm character. The current research of worm character can be classified into three categories: mathematical modeling of worm, emulation based on testbed, and package level worm simulation. However, in spite of the higher accuracy, the latter two methods require a high power of memory and computation, which poses a challenge to the large-scaled...
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