Announcements:

• The instructor's office hours for the rest of the semester will be: (1) April 26, Thursday (today), 1:30-2:30pm (2) April 27, Friday (tomorrow), 11am-12noon, and 1-2pm ,(3) May 4, Friday (the Friday before our project presentation), 10am-11am, 3:30-5:00pm.
• Grading criteria for midterm is released.
• Details about course project presentation have been added to the project page. The oral presentation will be on May 7, 2012, at 1:30-4:30pm in room 101 of Armory Building.
• Assignment 5 has now been officially released. It is due Thursday, April 19, 2012.
  
  
  
  
• Practice quesstions for preparing for the midterm exam are available here.
• A sample midterm and solutions is available here. Note that some questions (2(c) and 3) are out the scope of the topics that we will cover in our midterm.
• Assignment #4 is extended to Thursday Apr. 05.
• Assignment #4 is out.
• A detailed list of topics to be covered in the midterm is now available here.
• The due date of Part #3 of Assignment #3 has been extended to Thursday, March 29.
• Guidelines on how to finish project proposal reviews are now available here. Your reviews are due 11:59pm, Thursday, March 15.
• Assignment#3 training queries are released! Here are the query file and the relevance judgement file.
• Due date of part #2 of assignment #3 is extended to Sunday, Mar 04.
• Assignment #3 is out.
• Assignment #2 is out.
• Problem 3 of Assignment #1 has been revised to use a slightly different version of the CACM data set.

As the amount of online textual information (e.g., web pages, beblogs, tweets, email, news articles, office documents, and scientific literature) grows explosively, it is increasingly important to develop tools to help us manage and exploit the huge amount of information. Web search engines, such as Google and Bing, are good examples of such tools, and they are now an essential part of everyone's life. In this course, you will learn the underlying technologies of these and other powerful tools for managing and analyzing text information. You will be able to learn the basic principles and algorithms for managing, analyzing, and mining text data as well as obtain handson experience with using existing information retrieval toolkits to set up your own search engines and improving their search accuracy. You will also have an opportunity to work on a course project on a topic of your choice related to the course materials.

Unlike structured data, which is typically managed with a relational database, textual information is unstructured and poses special challenges due to the difficulty in precisely understanding natural language and users' information needs. In this course, we will introduce a variety of techniques for accessing and mining text information. The course emphasizes basic principles and pratically useful algorithms. Topics to be covered include, among others, text analysis, text retrieval, text categorization, text filtering, clustering, text data mining, search engine design and implementation, and applications in Web search and mining.

The course is lecture-based. Grading is based on both individual and group assignments, a late midterm examination, and a course project. Those who registered the course for 4 credit hours are required to finish a literature survey on a project-related topic. For more information about the course policy, please see " Basic Information" of the course.