Fig. 1: Vannevar Bush's Memex, a hypothetical electro-mechanical hypertext system described in 1945 and arguably the blueprint for modern information systems.
Description
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.
Logistics
- Location
- Gaines Hall, Room 5
- Time
- Monday & Wednesday, 16:00 – 17:30
Schedule
Note: Topics and speakers may change through the term as we adjust our course plan.
| Week | Day | Date | Topic | Materials | Discussant | HW |
|---|---|---|---|---|---|---|
| 1 | Mon | 4/1/2019 | Course Overview, Information-Seeking Behavior |
lecture_1.1a.pdf lecture_1.1b.pdf |
HW1 | |
| 1 | Wed | 4/3/2019 | No class - SDB giving workshop | lecture_1.2.pdf | ||
| 2 | Mon | 4/8/2019 | IR Basics | lecture_2.1.pdf | ||
| 2 | Wed | 4/10/2019 | IR Models: Boolean, Vector, Probablistic | lecture_2.2.pdf | HW2 | |
| 3 | Mon | 4/15/2019 | Index Construction/Optimization/Compression | lecture_3.1.pdf | ||
| 3 | Wed | 4/17/2019 | Experimental Evaluation | |||
| 4 | Mon | 4/22/2019 | Bayesian & Model-based approaches to evaluation | lecture_4.1.pdf | ||
| 4 | Wed | 4/24/2019 | Web Search, PageRank | |||
| 5 | Mon | 4/29/2019 | Search UI/UX | |||
| 5 | Wed | 5/1/2019 | User Behavior | |||
| 6 | Mon | 5/6/2019 | Pilot Study Presentations | |||
| 6 | Wed | 5/8/2019 | Machine Learning & Ranking | HW3 | ||
| 7 | Mon | 5/13/2019 | Relevance Feedback | |||
| 7 | Wed | 5/15/2019 | Query Suggestion/Reformulation | BiomedicalIR.pdf | ||
| 8 | Mon | 5/20/2019 | Multimedia Retrieval | |||
| 8 | Wed | 5/22/2019 | Document Clustering | |||
| 9 | Mon | 5/27/2019 | No class - SDB Traveling | |||
| 9 | Wed | 5/29/2019 | No class - SDB Traveling | |||
| 10 | Mon | 6/3/2019 | Microblog search | |||
| 10 | Wed | 6/5/2019 | Cross-Language IR | |||
| 11 | Mon | 6/10/2019 | Personalization: Time & Space | |||
| 11 | Wed | 6/13/2019 | Ethical Considerations in IR | |||
| 12 | Mon | 6/17/2019 | Project Presentations | |||
| 12 | Wed | 6/19/2019 | Project Presentations |
Assignments & Grading
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:
- A pilot study, and accompanying in-class presentation mid-way through the term;
- an in-class presentation at the end of the term of your final results;
- a conference-style writeup (8-10 pages not counting references).
Grading will be as follows:
- 30% Participation (including leading discussion)
- 30% Homework
- 40% Final project (including pilot study)
Textbooks
- Manning C, Raghavan P, and Schütze H. Introduction to Information Retrieval. Cambridge University Press, 2008. Available Online
- Hearst M. Search User Interfaces. Cambridge University Press, 2009. Available Online
Resources
Useful Books
- White, R. Interactions with Search Systems, Cambridge University Press, 2016.
- Baeza-Yates R, Ribeiro-Neto B. Modern Information Retrieval: The Concepts and Technology Behind Search, 2nd ed. Addison-Wesley, 2011. Some Chapters Available Online
- Case, D. Looking for Information: A Survey of Research on Information Seeking, Needs and Behavior, 3rd ed. Emerald Group Publishing, 2012.
- Grossman DA, Frieder O. Information Retrieval: Algorithms and Heuristics, 2nd ed. Springer Netherlands, 2004.
- Ingwersen P and Järvelin K. The Turn: Integration of Information Seeking and Retrieval in Context. Springer, 2005.
- Leskovec J, Rajaraman A, and Ullman J. Mining of Massive Data Sets, 2nd ed. Cambridge University Press, 2014. Available Online
Assigned Readings
Week 1, Monday: Course Overview, Information-Seeking Behavior
- Hearst Ch. 3
- Case Ch. 3
- Belkin NJ. Anomalous States of Knowledge as a Basis for Information Retrieval. Canadian journal of information and library science. 1980 Jan 1;5:133–43.
- Patterson ES, Roth EM, Woods DD. Predicting vulnerabilities in computer-supported inferential analysis under data overload. Cognition, Technology & Work. 2001;3(4):224–37.
Week 1, Wednesday: No class - SDB giving workshop
Week 2, Monday: IR Basics
Week 2, Wednesday: IR Models: Boolean, Vector, Probablistic
Week 3, Monday: Index Construction/Optimization/Compression
Week 3, Wednesday: Experimental Evaluation
Week 4, Monday: Bayesian & Model-based approaches to evaluation
Week 4, Wednesday: Web Search, PageRank
Week 5, Monday: Search UI/UX
Week 5, Wednesday: User Behavior
Week 6, Monday: Pilot Study Presentations
Week 6, Wednesday: Machine Learning & Ranking
Week 7, Monday: Relevance Feedback
Week 7, Wednesday: Query Suggestion/Reformulation
Week 8, Monday: Multimedia Retrieval
Week 8, Wednesday: Document Clustering
Week 9, Monday: No class - SDB Traveling
Week 9, Wednesday: No class - SDB Traveling
Week 10, Monday: Microblog search
Week 10, Wednesday: Cross-Language IR
Week 11, Monday: Personalization: Time & Space
Week 11, Thursday: Ethical Considerations in IR
Week 12, Monday: Project Presentations
Week 12, Wednesday: Project Presentations
Instructor
Steven Bedrick
Steven Bedrick can usually be found in his natural habitat, Gaines Hall room 19. While he has no set office hours, GH is far enough off the beaten path that you should probably schedule something with him before making the schlep.
We strongly encourage you to consult the Student Health Center for guidance about any pre-travel immunizations that may be required before visiting Gaines Hall.
Access Statement
Our program is committed to all students achieving their potential. If you have a disability or think you may have a disability (physical, learning, hearing, vision, psychological) which may need a reasonable accommodation please contact Student Access at (503) 494-0082 or e-mail studentaccess@ohsu.edu to discuss your needs. You can also find more information at http://www.ohsu.edu/student-access. Because accommodations can take time to implement, it is important to have this discussion as soon as possible. All information regarding a student’s disability is kept in accordance with relevant state and federal laws.
Equity and Inclusion
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