Title: Ranking Techniques: Representations, Algorithms and Applications
Abstract: Currently, ranking has emerged to be a central problem in many fields, and many problems traditionally formulated as rating prediction tasks can be reformulated as ranking problems. In this talk, I will introduce my recent work on the ranking techniques. Firstly, I will introduce the preliminaries, including the problem formulation, representations and basic ranking algorithms. Then secondly, I will provide some application examples to illustrate the advantages of the ranking-oriented algorithms. Finally, I will present the possible research issues in the future.
Bio: Shuaiqiang Wang is an Assistant Professor at University of Jyv?skyl? in Finland. He received Ph.D. and B.Sc. in Computer Science from Shandong University, China, in 2009 and 2004 respectively. He visited Hong Kong Baptist University as an exchange Ph.D. student at in 2009. He was a postdoctoral research associate at Texas State University in 2010, and an Associate Professor at Shandong University of Finance and Economics from 2011 to 2014. His research interests include recommender systems, information retrieval and data mining. He has published more than 30 papers in leading conferences like SIGIR, AAAI and CIKM, and journals like TKDE, TIST and JASIST. He served as a PC member for a number of conferences like SIGIR, IJCAI and CIKM, and a reviewer for journals like TOIS, TEC and IPM. The detailed information can be found from his homepage http://users.jyu.fi/~swang/.