中文摘要：

Xianfa Cai is an associate professor of the School of Medical Information Engineering, Guangdong Pharmaceutical University. Cai received his BS and MS degrees from Jiangxi Normal university and SunYat-sen University in 2002 and 2006, respectively, and obtained his PhD degree from South China University of Technology in 2013. His research focuses on machine learning, pattern recognition, and bioinformatics.E-mail： cxianfa@126.com Guihua Wen is a professor and doctoral supervisor. In 2005 and 2006, he did visiting research on machine learning and semantic web in School of Electronics and Computer, University of Southampton, UK. His main research interests are computational creativity, machine learning, knowl- edge discovery and cognitive geometry. Since 2006, he has proposed some original methods based on the computation of cognitive laws that can effectively solve difficult problems in information science. He has been a Council Member of Chinese Association for Artificial Intelligence and a program committee member of many international conferences. He is also a reviewer for China National Natural Science Foundation. Jia Wei received his BS and MS degrees in computer science from Harbin Institute of Technology in 2003 and 2006, respectively, and his PhD degree in computer science from the South China University of Technology in 2009. He is now a lecturer in the School of Computer Science and Engineering, South China University of Technology. His research fields include machine learning and image retrieval. Zhiwen Yu is a professor in the School of Computer Science and Engineering, South China University of Technology, Guangzhou, China. Yu is a senior member of IEEE and a senior member of China Computer Federation. He received his BS and MPhil from SunYat- sen University in China in 2001 and 2004, respectively, and his PhD degree in computer science from the City University of Hong Kong, China in 2008. His research interests include pattern recognition, bioinformatics, multimedia, intelligent computing, and da