COMP 790-090 Research Seminar (GNET 713 BCB Module) Spring 2008
Data Mining: Concepts, Algorithms, and Applications

With the unprecedented rate at which data is being collected today in almost all fields of human endeavor, there is an emerging economic and scientific need to extract useful information from it. Data mining is the process of automatic discovery of patterns, changes, associations and anomalies in massive databases, and is a highly inter-disciplinary field representing the confluence of several disciplines, including database systems, data warehousing, machine learning, statistics, algorithms, data visualization, and high-performance computing. This seminar will provide an introductory survey of the main topics (including and not limited to classification, regression, clustering, association rules, trend detection, feature selection, similarity search, data cleaning, privacy and security issues, and etc.) in data mining and knowledge discovery as well as a wide spectrum of data mining applications such as bioinformatics, E-commerce, environmental study, financial market study, multimedia data processing, network monitoring, social service analysis.

The first half of the semester will cover the principles and algorithms of data mining, while emphasis will be on performance issues and applications of data mining during the second half of the semester. The lectures are based on a collection of journal and conference papers and book chapters. A number of guest lectures by faculty members in other fields or other departments will be also scheduled.

Each student in COMP 790-90 will be expected to present a paper and lead the discussion following his/her presentation and do a project on selected topics. Students in GNET 713 need to attend the first nine lectures and do a project on selected topics. There will be neither homework nor exam.