Search Results - "Hu, Keyun"

Transcriptome analysis clarified genes involved in resistance to Phytophthora capsici in melon by Wang, Pingyong, Wu, Haibo, Zhao, Guangwei, He, Yuhua, Kong, Weihu, Zhang, Jian, Liu, Shuimiao, Liu, Mengli, Hu, Keyun, Liu, Lifeng, Xu, Yongyang, Xu, Zhihong

“…Phytophthora blight caused by Phytophthora capsici is a devastating disease for melon plant. However, the underlying resistance mechanisms are still poorly…”
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Efficient overlapping community detection in huge real-world networks by Wu, Zhihao, Lin, Youfang, Wan, Huaiyu, Tian, Shengfeng, Hu, Keyun

“…The detection of overlapping community structure in networks can give insight into the structures and functions of many complex systems. In this paper, we…”
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VisArchive: a time and relevance based visual interface for searching, browsing, and exploring project archives by Hu, Keyun, Staub-French, Sheryl, Tory, Melanie, Nepal, Madhav Prasad

“…Background Project archives are becoming increasingly large and complex. On construction projects in particular, the increasing amount of information and the…”
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SECTCS: towards improving VSM and Naive Bayesian classifier by Mingyu Lu, Keyun Hu, Yi Wu, Yuchang Lu, Lizhu Zhou

“…Based on the study of a text classification technique, we propose a new text classification method which improves the Vector Space Model and Naive Bayesian…”
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Boosting simple decision trees with Bayesian learning for text categorization by Lili Diao, Keyun Hu, Yuchang Lu, Chunyi Shi

“…Introduces a Bayesian method to select best base classifiers for a boosting algorithm that is used for solving text categorization problems. This method is…”
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Using boosting mechanism to refine the threshold of VSM-based similarity in text classification by Lili Diao, Keyun Hu, Yuchang Lu, Chunyi Shi

“…The vector space model (VSM)-based similarity classifier is the simplest text categorization method. It has a high classification speed, but with low accuracy…”
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New boosting algorithms for text categorization by Lili Diao, Mingyu Lu, Keyun Hu, Yuchang Lu, Chunyi Shi

“…AdaBoost.SZ is a boosting method specifically designed for solving multi-class, multi-label text categorization problems. Fabrizio Sebastiani et al. (2000)…”
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