How many information retrieval systems have you used since waking up this morning? Probably more than you think. Information retrieval systems, including but not limited to web search engines, product recommender systems, library catalogues, and social media applications represent vital tools for navigating our modern information ecosystem. The underlying algorithms and technologies that power these systems come from every corner of computer and information science, and have a rich and fascinating history.
In this course, we will study the art and science of information retrieval. We will cover a wide range of technical topics and applications of IR. Furthermore, because information is generally produced and consumed by humans, we will have a particular focus on issues surrounding human users of IR systems.
The course will not involve a final exam; however, it will involve a final project, which will include an in-class presentation as well as a formal written paper. There will also be several homework assignments, including a pilot study for the final project. Furthermore, students will be expected to present at least one paper in class as well as participate in class discussions. There will also be a considerable amount of reading assigned, which students will be expected to actually do.
Note: Topics and speakers may change through the term as we adjust our course plan.
|1||Mon||4/1/2019||Course Overview, Information-Seeking Behavior||
|1||Wed||4/3/2019||No class - SDB giving workshop||lecture_1.2.pdf|
|2||Wed||4/10/2019||IR Models: Boolean, Vector, Probablistic||lecture_2.2.pdf||HW2|
|4||Mon||4/22/2019||Bayesian & Model-based approaches to evaluation||lecture_4.1.pdf|
|4||Wed||4/24/2019||Web Search, PageRank|
|6||Mon||5/6/2019||Pilot Study Presentations|
|6||Wed||5/8/2019||Machine Learning & Ranking||HW3|
|9||Mon||5/27/2019||No class - SDB Traveling|
|9||Wed||5/29/2019||No class - SDB Traveling|
|11||Mon||6/10/2019||Personalization: Time & Space|
|11||Wed||6/13/2019||Ethical Considerations in IR|
Assigned readings for each session may be found below, grouped by week. Students are expected to have read each week's readings before class (excepting the first session), and to be prepared to discuss them in class. Most readings are available through the OHSU Library; we will provide copies of other articles as needed.
Additionally, students will be expected to take turns leading discussions (to be counted towards the participation component of the grade). The precise logistics of this will be determined once we know about the final enrollment.
There will be several hands-on homework assignments given throughout the class. Each assignment will come with a due date, which should be treated as firm. If you need an extension, please make your request by 5:00 PM two days prior to the assignment's due date. In other words, if an assignment is due on a Tuesday, extension requests must be made by Sunday afternoon. This is to help prevent procrastination, to give you time to come to me for help, and to help me plan my grading time.
In addition to homework assignments, there will be a final project on the subject of your choice. In the past, students have replicated a paper, implemented an algorithm or approach, added a feature to an existing IR system, participated in a shared task (TREC, CLEF, etc.), and so on. The deliverables for the project are:
Grading will be as follows:
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