Spring 2007 Data MiningCourse DescriptionPrerequisites:Visible Notes:Course SyllabusPart I. Introduction and Related TopicsPart II. Core TechniquesPart III. Advanced TopicsTextbook:References:Spring 2007 Data Mining Dr. Xiaoyan LiDepartment of Computer ScienceMount Holyoke Collegeemail: [email protected] phone: (413) 538-2554 Course DescriptionData Mining has become one of the most exciting and fastest growing fields in computer science.Data Mining refers to various techniques which can be used to uncover hidden information from a database. The data to be mined may be complex, multimedia data including text, graphics, video, audio and bioinformatics data. Data Mining has evolved from several areas including: databases, artificial intelligence, machine learning, pattern recognition, multimedia information retrieval, and can be applied to the exploration of hidden information from web, video, and bioinformatics data. This course is designed to provide senior undergraduate students with introductory of data mining concepts and tools. In addition, related concepts such as information retrieval, web mining and bioinformatics will be covered. Prerequisites:CS 211 and CS 221 or permission of instructorVisible Notes:2 meetings (75 minutes)Course Syllabus Part I. Introduction and Related Topics1. Introduction: tasks, issues, metrics and social implications2. Related topics in database: OLTP, OLAP and data warehousing3. Relate topics in information retrieval: web search, question-answering and novelty detection4. Related Topics in artificial intelligence: machine learning and pattern matchingPart II. Core Techniques1. Classification: Bayesian, KNN, ID3, ANN, rule-based2. Clustering: hierarchical, partitional, clustering in large database 3. Associate Rules: basic and advanced algorithmsPart III. Advanced Topics1. Web Mining: contents, structure and usage2. Image/Video Mining: CBIR, MPEG-7, video event detection3. Bioinformatics: biology preliminaries, information aspects, microarray data clustering Textbook: Data Mining Introductory and Advanced Topics by Margaret H. Dunham Prentice Hall, 2003 Book Web Page References:Data Mining: Multimedia, Soft Computing, and Bioinformatics, Sushmita Mitra, Tinku Acharya, ISBN: 0-471-46054-0, Hardcover, 424 pages, September 2003 http://www.wiley.com/WileyCDA/WileyTitle/productCd-0471460540.htmlPrinciple of Data Mining, by Hand, Mannila and Smith, MIT Press,