Discovering the relationship between protein sequence pattern and protein secondary structure is important for accurately predicting secondary structure of protein sequence. A protein secondary structure pattern dicti...
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In document-center XML dataset, an element may contain so many text that users have to spend enough time to judge the elements returned by XML search engine are valuable or not. Query-orient XML summarization system a...
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The aims of the workshop on Personalised Multilingual Hypertext Retri eval (PMHR) are twofold: to set the scene in this challenging area, allowing the different communities engaged in related research topics to meet a...
Search engine users often have clear search tasks hidden behind their queries. Inspired by this, the modern search engines are providing an increasing number of services to help users simplify their key tasks. However...
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Clustering is an important data analysis technique and it widely used in many field such as data mining, machine learning and pattern recognition. Ant colony optimization clustering is one of the popular partition alg...
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Domain terms play a crucial role in many research areas, which has led to a rise in demand for automatic domain terms extraction. In this paper, we present a two-level evaluation approach based on term hood and unit h...
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In many areas, a lot of data have been modeled by graphs which are subject to uncertainties, such as molecular compounds and protein interaction networks. While many real applications, for example, collaborative filte...
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In many areas, a lot of data have been modeled by graphs which are subject to uncertainties, such as molecular compounds and protein interaction networks. While many real applications, for example, collaborative filtering, fraud detection, and link prediction in social networks etc, rely on efficiently answering k-nearest neighbor queries (kNN), which is the problem of computing the most "similar" k nodes to a given query node. To solve the problem, in this paper a novel method based on measurement of SimRank is proposed. However, because graphs evolve over time and are uncertainly, the computing cost can be very high in practice to solve the problem using the existing algorithms of SimRank. So the paper presents an optimization algorithm. Introducing path threshold, which is suitable in both determined graph and uncertain graph, the algorithm merely considers the local neighborhood of a given query node instead of whole graph to prune the search space. To further improving efficiency, the algorithm adopts sample technology in uncertain graph. At the same time, theory and experiments interpret and verify that the optimization algorithm is efficient and effective.
Activity instance oriented handling is a new means for vertical optimization of process cases. Unlike our previous batch processing mechanism in workflows, it focuses on the data characteristics of activity instances ...
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