- A list of topics to be covered in the midterm is available here.
- Assignment 6 is now available.
- Assignment 5 is now available. You may work with one additional person on this assignment. Please start early if you can.
- Assignment 4 is now available.
- Assignment 3 is now available.
- Assignment 2 is now available.
- Assignment 1 is now available.
- The first class meeting is Aug. 24, 2016, Wed, in room 1109 Siebel Center.
This is a graduate-level course covering the major research topics in the growing field of information retrieval (IR). Briefly speaking, IR is the underlying science of search engines, but its broader goal is to help users management and make use of large amounts of text data. The impact of IR research is most visible from the recent dramatic growth of the Web search engine industry, but applications of IR research also go beyond search engines to text data mining, and intelligent information systems in general.
The goal of this course is: 1) to provide an in-depth introduction to the advanced concepts and techniques in information retrieval and text mining with an emphasis on formal frameworks and models for information retrieval , especially the use of statistical language models and machine learning techniques; 2) to provide the students with an opportunity to learn frontier topics through working on flexibly designed course projects and reading relevant papers; and 3) to give students enough training for doing research in IR or applying advanced IR technologies in practical applications.
The course will involve lectures by instructor, student presentations, and research projects on major research topics in information retrieval. There will be frequent but short assignments and a late midterm exam. Students are also required to finish a course project that can potentially lead to a publication or an innovative useful system. Group projects are allowed and encouraged.
Prerequisite: Students are expected to have a good knowledge of basic probability and statisticcs in addition to programming skills at the level of CS225 or a similar programming course. Some background in one or more of the following areas: information retrieval, machine learning, natural language processing, data mining, or databases would be a plus, but not required. If you are not sure whether you have the right background, please contact the instructor.