This seminar is an online seminar with no physical meetings. There will be no physical class meetings. All the activities will happen online at https://mediaspace.illinois.edu/channel/CS591TXT+Text+Mining+Seminar/
Students are expected to read, present, and discuss papers in the general area of text mining. Text mining is concerned with how to analyze large amounts of text data using computational methods to discover interesting patterns and useful knowledge to help people finish tasks more efficiently or more effectively, especially in optimization of decision making. We will read papers about text mining algorithms and applications. You may find more background about this topic from the following book:
ChengXiang Zhai and Sean Massung. 2016. Text Data Management and Analysis: a Practical Introduction to Information Retrieval and Text Mining. Association for Computing Machinery and Morgan & Claypool, New York, NY, USA.
The PDF file of the book is available at:
The format of the seminar is as follows: At the beginning of the semester, we will decide a list of candidate papers to read for the entire semester. We expect to cover anywhere from 20~40 papers depending on the number of the students in the class. Students would then be asked to sign up for the papers that they would like to present. Each student would be expected to present at least one paper and maybe more depending on the class size.
In the time period allocated to each paper, the student responsible for presenting the paper would read the paper in detail and record a voiced ppt presentation, which would be uploaded to the course media space (https://mediaspace.illinois.edu/channel/CS591TXT+Text+Mining+Seminar/).
All the other students are expected to post questions or comments about the paper using the “Comment” function on the media page. The presenting student is then expected to respond to the posted questions and comments to engage a discussion. The instructor would facilitate the discussion as needed. The discussion should be focused on understanding the motivation of the paper, assessing the novelty, digesting the key contributions, examining the soundness of the paper, and suggesting any ideas for further improving/extending the work or any applications of the techniques covered in a paper.
The grading will be based on completion, including 1) completing the assigned paper(s) for presentation; 2) participating in discussion of all papers, and 3) responding to comments/questions raised about the presented paper(s).
