The objective of this course is to get an overview of several advanced data mining techniques and understand the research methods applied in the field. It is assumed that students are familiar with the basic data mining topics (clustering, classification, and association rules) and have some experience with programming and one or more data mining tools (R, RapidMiner, Weka, XLMiner, etc.). Topics include Data Stream Mining, Opinion Mining in Natural Language Processing, Outlier Analysis, Bayesian Networks, Social Network Mining, and Big Data Technologies. Most recent research papers will be discussed in the class and a final paper or project will be presented in the class by each student.
Prerequisites
CS 430 or its equivalent