Yun Xiao

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MOTIVATION The accurate prediction of disease status is a central challenge in clinical cancer research. Microarray-based gene biomarkers have been identified to predict outcome and outperform traditional clinical parameters. However, the robustness of the individual gene biomarkers is questioned because of their little reproducibility between different(More)
This paper is about adopting the longest common subsequence (LCS) matching for Chinese information retrieval. We re-ranked the retrieved documents by a mixture of the original similarity score and the LCS score obtained by matching the document titles and the query. This LCS-based similarity score is also used in pseudo-relevance feedback in various ways(More)
In our formal runs, we have experimented with hybrid-term indexing and bigram indexing because hybrid-term indexing is a more distinct type of indexing strategy for better pooling and because bigram indexing usually gives robust (near) good results. We have also used our pseudo-relevance feedback (PRF) methods. In the informal runs, we have experimented(More)
Based on the Small-World model of CAS e-Science and the power low of Internet, this paper presents a scalable CAS e-Science Grid framework based on virtual region called Virtual Region Grid Framework (VRGF). VRGF takes virtual region and layer as logic manage-unit. In VRGF, the mode of intra-virtual region is pure P2P, and the model of inter-virtual region(More)