The social networks with the complex user relations and huge amount of data and hidden information, bring new opportunities and challenges for the study of information diffusion and influence maximization. In recent y...
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UL1741 rules that to realize the islanding detection, the inverter must stop running within 2s after the main grid failure occurs. However, with the increasing of the capacity of distributed generation system, in orde...
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Under the influence of multipath effects and small scale fading, the robustness and reliability of the existing human detection methods based on radio frequency signals are easy to be impaired. In this paper, we propo...
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According to the characteristics of positive and negative edge of signed networks, a new signed networks community detection algorithm BTCN-SNCD (Signed networks Community Detection Based on the Tightness of Common Ne...
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In this letter, new methods of constructing quaternary sequence pairs are presented based on binary sequence pairs with two-level autocorrelation, almost perfect binary sequence pairs and cyclic shift sequences. The q...
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The structure of complex software systems can be extracted as a complex software network, and the quality of software systems largely depends on the topological structure of the software network. A small portion of im...
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Identifying influential nodes is crucial for understanding and improving the stability and robustness of complex software network. This paper presents a new method based on LeaderRank information to identify top-k inf...
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It is well known that the drawbacks of label propagation algorithm are high randomness, weak robustness and easy to form monster community. Many improved methods are proposed constantly in order to avoid these problem...
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In this paper, we focus on efficient construction of restricted subtree （RSubtree） results for XML keyword queries on a multicore system. We firstly show that the perfor- mance bottlenecks for existing methods lie i...
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In this paper, we focus on efficient construction of restricted subtree （RSubtree） results for XML keyword queries on a multicore system. We firstly show that the perfor- mance bottlenecks for existing methods lie in 1） computing the set of relevant keyword nodes （RKNs） for each subtree root node, 2） constructing the corresponding RSubtree, and 3） parallel execution. We then propose a two-step generic top-down subtree construction algorithm, which computes SLCA/ELCA nodes in the first step, and parallelly gets RKNs and generates RSubtree results in the second step, where generic means that 1） our method can be used to compute dif- ferent kinds of subtree results, 2） our method is independent of the query semantics; top-down means that our method con- structs each RSubtree by visiting nodes of the subtree con- structed based on an RKN set level-by-level from left to right, such that to avoid visiting as many useless nodes as possible. The experimental results show that our method is much more efficient than existing ones according to various metrics.
In this paper, we try to systematically study how to perform doctor recommendation in medical social net- works （MSNs）. Specifically, employing a real-world medical dataset as the source in our work, we propose iBol...
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In this paper, we try to systematically study how to perform doctor recommendation in medical social net- works （MSNs）. Specifically, employing a real-world medical dataset as the source in our work, we propose iBole, a novel hybrid multi-layer architecture, to solve this problem. First, we mine doctor-patient relationships/ties via a time-constraint probability factor graph model （TPFG）. Second, we extract network features for ranking nodes. Finally, we propose RWR- Model, a doctor recommendation model via the random walk with restart method. Our real-world experiments validate the effectiveness of the proposed methods. Experimental results show that we obtain good accuracy in mining doctor-patient relationships from the network, and the doctor recommendation performance is better than that of the baseline algorithms： traditional Ranking SVM （RSVM） and the individual doctor recommendation model （IDR-Model）. The results of our RWR-Model are more reasonable and satisfactory than those of the baseline approaches.
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