Grades

Grades for this class will be based on class participation, three homeworks, a presentation, and a semester project.

1.

Class Participation. Because this is a seminar class, the lectures will be interactive. No exams will be given to test your knowledge of the material. Instead, I will expect you to participate in class discussions. Understanding of the material will be demonstrated by asking and answering questions, and by providing insights and opinions on the topics covered each class period.

2.

Paper Presentation. Each student will have an opportunity to research and present one paper in class. Presentation days and suggested papers are available on the class home page. The presentation will be graded based on the following qualities: 1) understanding of the material, 2) clarity and professionalism of the presentation, 3) ability to field questions on the topic, 4) assessment of the approach analyzing the strengths, weaknesses, and future ideas, and 5) outside research on the topic, bringing in material from additional papers, demonstrate of the technique, and so forth. The presentations will be approximately 20 minutes long.

As an alternative to a paper presentation, students may form teams of two or three and research a particular Data Mining tool. Sample tools are listed on the home page. The suggested team size is listed with each tool, the quality and thoroughness of the presentation should be proportional to the team size. Tool presentations will include an overview of the product, a demonstration of its usage, and an assessment of the strengths and weaknesses of the tool. Once again, integrating outside research on the tool, its algorithms and its usages, will be a factor in the grade.

Please email your top three choices for presentation topic and/or day to cook@cse.uta.edu by September 2. A final schedule will be posted by September 7. You are welcome to suggest papers or tools not on the list, but these choices must be approved by the professor.

3.

Semester Project. The ideas presented in class will be grounded through the class project. The project will involve implementation of a data mining technique, improvement of an existing algorithm, or a novel application of a data mining algorithm. A one-page project proposal is due in class or through email by October 26. The project is due at 5:30 on December 2 (the last day of class), along with a writeup (less than 15 pages) describing your system and the results.