Big Data Analytics in Business Environments  

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Big Data Analytics in Business Environments
( 2016-01-12 )


Speaker: Prof. Hui Xiong
Time: 2015-07-05 9:00
Place: Room 117, West Building of Science and Technology, West Campus

Recent years have witnessed the big data movement throughout all the business sectors. As a result, awareness of the importance of data mining for business is becoming wide spread. However, the big data are usually immense, fine-grained, diversified, dynamic, and sufficiently information-rich in nature, and thus demand a radical change in the philosophy of data analytics. In this talk, we introduce a set of scenarios for understanding and mining of business data in various business sectors. In particular, we will discuss the technical and domain challenges of big data analytics in business environments. The theme to be covered will include (1) the data mining problem formulation in different business applications, such as marketing, real estate, and mobile intelligence; (2) the challenging issues of data pre-processing and post-processing in business analytics;(3) how the underlying computational models can be adapted for managing the uncertainties in relation to big data process in a huge nebulous business environment. Finally, we will also show some promising research directions.

Short Bio:
Dr. Hui Xiong is currently a Full Professor and the Director of Rutgers Center for Information Assurance at Rutgers, the State University of New Jersey, where he received a two-year early promotion/tenure (2009), the Rutgers University Board of Trustees Research Fellowship for Scholarly Excellence (2009), and the ICDM-2011 Best Research Paper Award (2011). Dr. Xiong received his Ph.D. in Computer Science from the University of Minnesota (UMN), USA, in 2005, the B.E. degree in Automation from the University of Science and Technology of China (USTC), China, and the M.S. degree in Computer Science from the National University of Singapore (NUS), Singapore. His general area of research is data and knowledge engineering, with a focus on developing effective and efficient data analysis techniques for emerging data intensive applications. He has published prolifically in refereed journals and conference proceedings (3 books, 60+ journal papers, and 80+ conference papers). He is the co-Editor-in-Chief of Encyclopedia of GIS by Springer, and an Associate Editor of IEEE Transactions on Knowledge and Data Engineering (TKDE), ACM Transactions on Management Information Systems, as well as IEEE Transactions on Big Data. He has served regularly on the organization and program committees of numerous conferences, including as a Program Co-Chair of the Industrial and Government Track for the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD),a Program Co-Chair for the IEEE 2013 International Conference on Data Mining (ICDM-2013), and a General Co-Chair for the IEEE 2015 International Conference on Data Mining (ICDM-2015). He is an ACM Distinguished Scientist.