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Titlebook: Advances in Data and Web Management; Joint 9th Asia-Pacif Guozhu Dong,Xuemin Lin,Jeffrey Xu Yu Conference proceedings 2007 Springer-Verlag

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https://doi.org/10.1007/978-94-010-1786-2l conformation of proteins. Currently, most predictors are based on machine learning approaches with a short fixed-size input window scanning over the amino acid sequence. The center of the window corresponds to the prediction site where the prediction is performed by utilizing the properties of nei
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Sensing and Objective Reference,urate classification. In both processes, we apply the idea of local page group structure. The rough filtering comprehensively gathers all potential homepages from the web with as few noise pages as possible. It uses property-based keyword lists according to four page group models that are based on t
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https://doi.org/10.1007/978-3-030-53088-4aningful sentences relevant to a given topic. The proposed method decomposes a sentence into the linear combination of sparse non-negative semantic features so that it can represent a sentence as the sum of a few semantic features that are comprehensible intuitively. It can avoid extracting the sent
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https://doi.org/10.1007/978-3-540-72524-4Extensible Markup Language (XML); Path; Routing; classification systems; data engineering; data managemen
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978-3-540-72483-4Springer-Verlag Berlin Heidelberg 2007
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https://doi.org/10.1007/978-94-011-4393-6gh experimental study shows that IMCS outperforms the state-of-the-art algorithms – PrefixSpan, CloSpan, BIDE and a recently proposed incremental mining algorithm IncSpan by about a factor of 4 to more than an order of magnitude.
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https://doi.org/10.1007/978-94-010-1786-2om the center residue. We have studied on how the prediction performance can be affected by imposing different weights on the features according to the distance of residues from the center residue, and in this work, we propose an adaptive weighting scheme to improve prediction accuracy.
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