IMT-542: Principles of Information Retrieval (IR) Systems

Course Description

Information Retrieval (IR) is a really HOT subject these days. All thanks to the World Wide Web, Web Search, and our friends at Google, Yahoo!, MSN, and all the other search engines that have come and gone!!! But, there's a lot that happens between the typing of 2-3 keywords in a small box at the User Interface, and receiving the results. In the next ten weeks we'll look at issues surrounding information retrieval systems. We will examine information system design and evaluation issues, and look under the hood of the search engines to pick at what's going on and why.

...another way to say the above is that:

The course "Principles of Information Retrieval Systems" provides an integrated view of information retrieval (IR). It covers IR theories and models for text, hypermedia and the web, and reviews user-centered and system-centered approaches. A variety of issues involved in the design, development, and evaluation of search engines are examined.

Objectives

The course goals are that you:

· become familiar with basic issues and current practice in IR

· familiarize yourselves with IR tools

· review important research in IR.

Methods:

Lectures by instructor, students and guest speakers, Readings, Assignments, Project, and Labs.

Readings need to be completed prior to class meeting.

Recommended Texts:

Christopher D. Manning, Prabhakar Raghavan, & Hinrich Schütze. Introduction to Information Retrieval, Cambridge University Press. 2007. eBook available at: http://www-csli.stanford.edu/~schuetze/information-retrieval-book.html

Belew, R.K. Finding out about--A cognitive perspective on search engine technology and the www. Cambridge University Press, 2000. http://www.cse.ucsd.edu/~rik/foa/ or https://projects.ischool.washington.edu/efthimis/uwnetid/courses/readings/FindingOutAbout/foa/contents.htm;

Additional readings are also required and specified in the syllabus.

Readings need to be completed prior to class meeting.

Lab Links:

IRtoolbox

Communication tools

Course website

http://courses.washington.edu/imt542e

Find the weekly readings, assignments and announcements

Course Listserv

imt542a_au07@u.washington.edu

Registered students are subscribed automatically using their UW email account. This is the official medium of communication between instructors and students. Course related announcements and answers to student questions are posted on this list.

Collect It area for assignments (Please submit assignments by 12pm of the due date)

https://catalysttools.washington.edu/collectit/dropbox/efthimis/552

Anonymous Feedback

http://catalyst.washington.edu/webtools2/umail/index.cgi?owner=efthimis&id=1740

Submit questions and comments to the instructors anonymously.

Prerequisites: imt540 or instructor's consent

Credits: 3, graded

Lectures: Th 4:30-8:20pm MGH 420

Lab: Th 6:30-8:30pm MGH 430

Instructor: Efthimis N. Efthimiadis

Office Hours: Thu 7:00-8:00pm and Rm MGH 330S by appointment.

Telephone: 206-616-6077

Email: efthimis@u.washington.edu

Grading:

(a) Assignments and Labs 40%

(b) Project 60%

Total: 100%

(a) Labs

A series of labs will start in class and will have to be completed individually after class. These will introduce students to the retrieval software and to utilities for text manipulation.

(b) Assignments

See handouts or links

Assignment #1: Google, Yahoo, Ask, Live search exercise; DUE: on week 2

Assignment #2: Document Analysis and Inverted files DUE: on week 3

Assignment #3: Using the IR Toolbox: Tokenization and Stemming DUE: on week 4

Assignment #4: Using the IR Toolbox to search an index DUE: on week 6

Assignment #5: Using the IR Toolbox: Conduct a simple IR system performance experiment DUE: on week 7

(c) Project

See project handout -- TBA

Please note that the project has deliverables throughout the querter, some of which conflict with assignment deadlines.

Below you'll find the syllabus, which is a living/growing document!

Date Topic – AT A GLANCE

9/27-- Week 1

Introduction to IR. Overview of the components of an IRS. Queries, Documents, Indexing. Theories & Models in IR (Retrieval Techniques) for text, hypermedia, web.

Assignment.1 given;

10/4-- Week 2

Exploring Google search… Queries and Information Needs.

Document Analysis. Structure of documents, parsing, stemming, morphological analysis, tokenization.

Assignment.1 due; Assignment.2 and 3 given

10/11 -- Week 3

Retrieval Techniques. Exact Match vs. Partial Match Weighted Ranked Retrieval, Vector Space & Probabilistic retrieval models. Relevance Feedback.

Guest Speaker: Kevyn Collins-Thompson (CMU), <ENE - away>

Assignment.2 due;

10/18-- Week 4

Retrieval Techniques. (continued).

Retrieval Techniques. Exact Match vs. Partial Match Weighted Ranked Retrieval, Vector Space & Probabilistic retrieval models. Relevance Feedback.

Query Processing for IR (Query Formulation, ~ Expansion, and ~ Refinement)

Assignment.3 due; Assignment.4 given

10/25-- Week 5

Web search. Hypertext. Internet Search Engines. Link Analysis.

Guest Speaker: Erik Selberg, Amazon

Assignment.4 due;

11/1-- Week 6

Evaluation of IRS. Performance Measures. Relevance. Testing and test collections (testbeds, e.g., TREC test collections), User centered evaluation of IR systems.

Assignment.5 given

11/8-- Week 7

Evaluation of IRS (continued). Evaluating Exploratory Search Systems.

Guest Speaker: Ryen White, Microsoft Research. <ENE - away>

Assignment.5 due;

11/15-- Week 8

Web search (continued). Crawlers, Web graph. Log Analysis, evaluation revisited

11/22-- Week 9

NO CLASS - Thanksgiving Holiday

11/29-- Week 10

Faceted Search; Social tagging and bookmarking; Personalization.

12/6-- Week 11

Presentations. Review & Wrap-up

SYLLABUS

For the first day of class please do the READING assignment below. The first day we'll also have a discussion of the syllabus, topics of interest to you, and the term projects.

Date Topic Readings need to be completed prior to class meetings.

Week 1

Introduction to IR. Overview of the components of an IRS. Queries, Documents, Indexing. Theories & Models in IR (Retrieval Techniques) for text, hypermedia, web.

For class discussion:

When reading the articles by Vannenar Bush and Bruce Croft I'd like you to view them in perspective. As you read identify the "information system" issues raised and the solutions proposed. Reflect on the proposed solutions and compare them to present time issues and proposed solutions. Ponder a bit on the issues by removing the "technology" and focusing on the problems. How do the issues/problems of then and now compare?

The Belew "Chapter 1: Overview" provides a very nice overview of the IR problem.

Read:

1) Bush, Vannevar. As we may think. The Atlantic Monthly, July, 1945. (reprinted in ACM CHI Interactions, March 1996) http://www.theatlantic.com/doc/194507/bush

2) Croft, W.B. (1982) An overview of information systems. Information Technology: Research and Development, v.1, pp.73-96. https://projects.ischool.washington.edu/efthimis/uwnetid/courses/readings/Croft_Overview_of_IS.pdf

Optional:

(The Sparck Jones & Peter Willett readings provide a good background of research in IR in the past 50+ years. The Belew "Chapter 1: Overview" provides a very nice overview of the IR problem.)

3) Belew, R.K. Finding out about--A cognitive perspective on search engine technology and the www. Cambridge University Press, 2000. chapter 1: Overview;

4) Elizabeth Liddy. How a Search Engine Works. Searcher, vol 9, no. 5, May 2001. http://www.infotoday.com/searcher/may01/liddy.htm

5) Sparck Jones, Karen & Peter Willett, eds. Readings in Information Retrieval. Morgan Kaufmann, 1997. [Ch. 1: Introduction] [Ch. 2: History] [Ch. 3: Key Concepts]

Lecture Notes: slides

Assignment #1: Google, Yahoo, Ask, Live search exercise; due on week 2

Week 2

Exploring Google search… Queries and Information Needs.

Document Analysis. Structure of documents, parsing, stemming, morphological analysis, tokenization.

Assignment.1 due; Assignment.2 given

Read:

1. Google search.
a) Review of Google http://www.searchengineshowdown.com/features/google/review.html

b) Google Advanced Operators http://www.google.com/help/operators.html

2. Queries, Query Classification, and Search
Broder, A. 2002. A taxonomy of web search. SIGIR Forum 36, 2 (Sep. 2002), 3-10. DOI= http://doi.acm.org/10.1145/792550.792552

(skim) Rose, D. E. and Levinson, D. 2004. Understanding user goals in web search. In Proceedings of the 13th international Conference on World Wide Web (New York, NY, USA, May 17 - 20, 2004). WWW '04. ACM Press, New York, NY, 13-19. DOI= http://doi.acm.org/10.1145/988672.988675

3. Manning et al. Chapter 1: Information retrieval using the Boolean model.

4. Manning et al. Chapter 2: The dictionary & postings lists

Optional:

Belew chapter 2: Extracting Lexical Features

How Internet Search Engines Work. http://www.howstuffworks.com/search-engine.htm/printable

Porter, M.F. An algorithm for suffix stripping. Program, 14(3): 130-137, 1980. The stemmer is available at Martin Porter’s official website: http://www.tartarus.org/~martin/PorterStemmer/

Further reading:

Frakes & Baeza-Yates, Chapter 7: Lexical analysis & stopwords

Frakes & Baeza-Yates, Chapter 8: Stemming algorithms

Assignment #2: Document Analysis and Inverted files due on week 3

Assignment #3: Using the IR Toolbox: Tokenization and Stemming due on week 4

Lecture Notes: slides

Week 3

Retrieval Techniques. Exact Match vs. Partial Match Weighted Ranked Retrieval, Vector Space & Probabilistic retrieval models. Relevance Feedback.

Guest Speaker: Kevyn Collins-Thompson (CMU)

Read:

Maron, M. E. 1982. Probabilistic approaches to the document retrieval problem. In Proceedings of the 5th Annual ACM Conference on Research and Development in information Retrieval (West Berlin, Germany, May 18 - 20, 1982). Annual ACM Conference on Research and Development in Information Retrieval. Springer-Verlag New York, New York, NY, 98-107.

Manning et al. Chapter 6: Term weighting & vector space models

Manning et al. Chapter 11: Probabilistic information retrieval

Optional:

Background reading for understanding the IDF, RSJ - F4, and BM25 weighting schemes is available at http://www.soi.city.ac.uk/~ser/idf.html.

A discussion of the Okapi BM25 probabilistic model and links to papers is available from http://www.soi.city.ac.uk/~ser/blockbuster.html

S. Robertson, H. Zaragoza and M. Taylor, Simple BM25 extension to multiple weighted fields. CIKM 2004, Washington, DC, November 2004. In: D.A. Evans et al. (eds), CIKM 2004. ACM, 2004. (pp 42-49). Available from: http://portal.acm.org/citation.cfm?id=1031171.1031181

Belew chapter 3: Weighting and Matching against Indices & 5

-------------------------------------

Check here how LUCENE implements the class SIMILARITY (tf.idf)

Apache Lucene - Scoring
http://lucene.apache.org/java/docs/scoring.html

Changing Scoring -- Expert Level
http://lucene.apache.org/java/docs/api/org/apache/lucene/search/package-summary.html#scoring

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Lecture Notes: slides

Assignment #2 is DUE

Assignment #3: Using the IR Toolbox: Tokenization and Stemming due on week 4

Week 4

Retrieval Techniques. (continued).

READ:

Efthimiadis, E.N. "Query Expansion." In: Williams, Martha E., ed. Annual Review of Information Systems and Technology, v31, pp 121-187, 1996.

Ruthven, I. and Lalmas, M. A survey on the use of relevance feedback for information access systems. The Knowledge Engineering Review, Vol. 18:2, 95–145. 2003, Cambridge University Press. DOI: 10.1017/S026988890300063

Manning et al. Chapter 9: Relevance feedback & query expansion

Lecture Notes: slides

Assignment #3: is due

Assignment #4: Using the IR Toolbox to search an index DUE: on week 6

Assignment #5: Conduct a simple IR system performance experiment DUE: on week 7

Week 5

Topic: Link analysis and web search

Guest Speakers:
Erik Selberg, Amazon

Readings:

Review chapters 19-20-21 in the Manning, Raghavan, Schutze book http://www-csli.stanford.edu/~schuetze/information-retrieval-book.html

Ricardo Baeza-Yates, Carlos Castillo, Flavio Junqueira, Vassilis Plachouras, Fabrizio Silvestri. "Challenges on Distributed Information Retrieval." To appeared in: 2007 IEEE 23rd International Conference on Data Engineering (ICDE 2007).

Optional:

Skim through the following:

Baeza-Yates, R. & B. Ribeiro-Neto. eds. Modern Information Retrieval. ACM Press, 1999. Ch. 13: Web

(This chapter, though seemingly dated, is an excellent review of the issues surrounding web search. Read this first.)

Google Search Engine Architecture:

Brin, Sergei and Page, Laurence. (1998). The anatomy of a search engine. Paper presented at the Seventh International World Wide Web (WWW7) Conference, Brisbane, Australia. Available at http://dbpubs.stanford.edu:8090/pub/1998-8 and http://wwwdb.stanford.edu/~backrub/google.html

Barroso, L. A., Dean, J., & Hšlzle, U. (2003 ). Web Search for a Planet: The Google Cluster Architecture IEEE Micro, 23(2), 22-28. Retrieved December 20, 2004, from http://dx.doi.org/10.1109/MM.2003.1196112

Resources:

PageRank:
Ian Rogers. (2002). The Google Pagerank Algorithm and How It Works http://www.iprcom.com/papers/pagerank/index.html

RankNet (The MSN/Live algorithm):
C.J.C. Burges, T. Shaked, E. Renshaw, A. Lazier, M. Deeds, N. Hamilton, G. Hullender, "Learning to Rank using Gradient Descent", 22nd International Conference on Machine Learning, Bonn, 2005

Crawlers:
Martijn Koster, (1999). Robots in the web: threat or treat ? ConneXions, 4(4) http://www.robotstxt.org/wc/threat-or-treat.html

Allan Heydon and Marc Najork. (1999) “Mercator: A Scalable, Extensible Web Crawler", World Wide Web", 2(4), 219-229. http://citeseer.ist.psu.edu/heydon99mercator.html

Mercator web crawler: http://mercator.comm.nsdlib.org/

The WIRE Crawler website: http://www.cwr.cl/projects/WIRE/

Resource: The Web Robots Pages: http://www.robotstxt.org/wc/robots.html

Lecture Notes: slides

Lab: work on project

Week 6

Topic: Evaluation of IRS. Performance Measures. Relevance. Testing and test collections (testbeds, e.g., TREC test collections), User centered evaluation of IR systems.

Readings

Manning et al. Chapter 8: Evaluation in information retrieval

Richard Belew, 2000. Finding out about. Chapter 4. Assessing the Retrieval

The Text REtrieval Conference. In:Voorhees, Ellen M. and Donna K. Harman, eds. 2005. TREC: Experiment and Evaluation in Information Retrieval. MIT Press.

Optional:

Sparck Jones, Karen and Peter Willett, eds. (1997). Readings in Information Retrieval. Morgan Kaufmann, 1997. [Ch. 4: Evaluation]

Sparck Jones, Karen. (2000). Further reflections on TREC. Information Processing and Management, 36(1), 2000, page 37-85

Cleverdon, C.W. The significance of the Cranfield tests on index languages. In: Bookstein, A. et al. (eds.) Proceedings of the 14th Annual International ACM/SIGIR Conference on Research and Development in information retrieval. Chicago , IL . Oct. 13-16, 1991. pp3‑12.

David Hawking, Nick Craswell, Donna Harman (1999) Results and Challenges in Web Search Evaluation http://www8.org/w8-papers/2c-search-discover/results/results.html

LAB : work on project, and Assignment #5: Conduct a simple IR system performance experiment

Lecture Slides: pdf

Week 7

Topic: Evaluation of IRS (continued). Evaluating Exploratory Search Systems.

Guest Speaker: Ryen White, Microsoft Research

Readings

Manning et al. Chapter 8: Evaluation in information retrieval

Richard Belew, 2000. Finding out about. Chapter 4. Assessing the Retrieval

LAB : work on project, and Assignment #5: Conduct a simple IR system performance experiment

Lecture Slides: pdf

Week 8

Topic: Web graph. Web Search Analytics. Log Analysis.

READ:

Baeza-Yates, R., Castillo, C., & Efthimiadis, E. N. (2007). Characterization of National Web Domains. ACM Transactions on Internet Technology, 7(2), Article 9, 32 pages. http://doi.acm.org/10.1145/1239971.1239973

Visualization for IR

READ:

Baeza-Yates, R. & B. Ribeiro-Neto. eds. (1999). Modern Information Retrieval. ACM Press, 1999. [Ch. 10: User Interfaces]

Turetken, O. and Sharda, R. Visualization of web spaces: state of the art and future directions. SIGMIS Database 38, 3, July, 2007, 51-81. pdf

Koshman, S. Visualization-based information retrieval on the Web, Library & Information Science Research Volume 28, Issue 2, , Summer 2006, 192-207.
pdf

Check these Search Engines:

http://live.grokker.com or http://www.grokker.com
http://www.mooter.com/
http://www.webbrain.com
http://www.pagebull.com
http://www.snap.com - the enhanced search
http://kids.quintura.com/
http://www.quintura.com
http://www.kartoo.com

Week 9
Topic: Faceted Search. Social Tagging and Bookmarking. Personalization.
Faceted Search:
Yee, K-P., Swearingen, K., Li, K., and Hearst, M., Faceted Metadata for Image Search and Browsing, in CHI 2003. The Flamenco website is available at: http://flamenco.berkeley.edu try the demos.
Hearst, M, Divoli, A, Guturu, H, Ksikes, A, Nakov, P, Wooldridge, MA, and Ye, J. BioText Search Engine: beyond abstract search, Bioinformatics, June, 2007. The website available at: http://biosearch.berkeley.edu/

Personalization & Implicit Feedback:
Kelly, D. and Teevan, J. 2003. Implicit feedback for inferring user preference: a bibliography. SIGIR Forum 37, 2 (Sep. 2003), 18-28. DOI= http://doi.acm.org/10.1145/959258.959260

Teevan, J., Dumais, S. T. and Horvitz, E. (2005). Beyond the commons: Investigating the value of personalizing Web search. In Proceedings of the Workshop on New Technologies for Personalized Information Access (PIA). http://citeseer.ist.psu.edu/teevan05beyond.html

Fox, S., Karnawat, K., Mydland, M., Dumais, S., and White, T. 2005. Evaluating implicit measures to improve web search. ACM Trans. Inf. Syst. 23, 2 (Apr. 2005), 147-168. DOI= http://doi.acm.org/10.1145/1059981.1059982

Qiaozhu Mei and Kenneth Church. (2008). Entropy of Search Logs: How Hard is Search? With Personalization? With Backoff? In: First ACM International Conference on Web Search and Data Mining (WSDM 2008 ).

Social Tagging and Bookmarking.

Paul Heymann, Georgia Koutrika and Hector Garcia-Molina. (2008). Can Social Bookmarks Improve Web Search? In: First ACM International Conference on Web Search and Data Mining (WSDM 2008 ).

Project: work on & review

Week 10

Wrap-up

Project Presentations

Resources:

The list of readings below is given as a resource.

Baeza-Yates, R. & B. Ribeiro-Neto. eds. Modern Information Retrieval. ACM Press, 1999. [Ch. 10: User Interfaces [Ch. 13: Web ]

Belew, R.K. Finding out about--A cognitive perspective on search engine technology and the www. Cambridge University Press, 2000.

Borgman, C.L. (1999). What are digital libraries? Competing visions. Information Processing & Management, 35(3):227-243.

Brin, Sergei and Page, Laurence. 1998. The anatomy of a search engine. WWW7 conference. Available at http://www7.scu.edu.au/programme/fullpapers/1921/com1921.htm

Croft, W.B. 1995. What Do People Want from Information Retrieval? (The Top 10 Research Issues for Companies that Use and Sell IR Systems). http://www.dlib.org/dlib/november95/11croft.html

DL. Proceedings of the ACM International Conference on Research and Development in Digital Libraries. ACM Press. Available online through the ACM Digital Library.

Efthimiadis, E.N. "Query Expansion." In: Williams, Martha E., ed. Annual Review of Information Systems and Technology, v31, pp 121-187, 1996.

Frakes, W.B. & Baeza-Yates, R. eds. Information Retrieval: Data Structures & Algorithms. Englewood Cliffs, NJ: Prentice Hall, 1992.

Korfage, Robert. Information Storage and Retrieval. John Wiley & Sons, 1997.

Lesk, Michael. Practical Digital libraries: Books, Bytes & Bucks. Morgan Kaufmann, 1997

Manning, Christopher D. and Hinrich Schutze. Foundations of Statistical Natural Language Processing. MIT Press, 1999.

Manning, Christopher D., Prabhakar Raghavan, & Hinrich Schütze. Introduction to Information Retrieval, Cambridge University Press. 2007. eBook available at: http://www-csli.stanford.edu/~schuetze/information-retrieval-book.html

Maybury, Mark, ed. Intelligent Multimedia Information Retrieval. AAAI Press & MIT Press, 1997.

Meadow, C.T., Boyce, B.R., Kraft, D.H. Text Information Retrieval Systems. 2^nd edition. San Diego: Academic Press, 2000.

Porter, M.F. An algorithm for suffix stripping. Program, 14(3): 130‑137, 1980.

Salton, G. and McGill, M. Introduction to Modern Information Retrieval. McGraw-Hill, 1983.

Salton, G. Automatic Text Processing: the transformation, analysis, and retrieval of information by computer. Addison-Wesley, Reading, Mass. 1989.

SIGIR. Proceedings of the ACM SIGIR International Conference on research and Development in Information Retrieval. ACM Press. Available online through the ACM Digital Library.

Sparck Jones, Karen Information Retrieval Experiment. London: Butterworths, 1981. (There's a special issue on evaluation in "Information Processing & Management" in 1991.)

Sparck Jones, Karen and Peter Willett, eds. Readings in Information Retrieval. Morgan Kaufmann, 1997. [Ch. 1: Introduction] [Ch. 2: History] [Ch. 3: Key Concepts] [Ch. 4: Evaluation]

Stern, David, ed. Digital Libraries: Philosophies, technical design considerations, and example scenarios. New York: Haworth Press, 1999.

TREC: Text Retrieval Conference Proceedings. Vol. 1-8, edited by Donna Harman. National Institute for Science and Technology. 1992-1999. Available online at http://trec.nist.gov

van Rijsbergen, C.J. Information Retrieval. Butterworths, London and Boston, 2nd edition, 1979. (Available in electronic form on the fileserver “courses/lis544”)

Witten, Ian et al. Managing Gigabytes. Orlando, FL: Morgan-Kaufmann-Publishers-Incorporated, 1999.

Student services

Wendie Phillips

Director of Student Services
470E Mary Gates Hall

wrp@u.washington.edu
Tel: (206) 616-8553

Please note: If you have any concerns about a course please contact the instructor Efthimis Efthimiadis directly at efthimis AT u.washington.edu

If you are still not satisfied with the response that you receive, you may contact Matt Saxton, the Associate Dean for Academics in 370 Mary Gates Hall, by phone at : (206) 685-9626, or by e-mail at msaxton@u.washington.edu.

You may also contact the Graduate School at G-1 Communications Building, by phone at (206) 543-5900, or by e-mail at efeetham@u.washington.edu

Students with Disabilities

To request academic accommodations due to a disability, please contact Disabled Student Services: 448 Schmitz, 206-543-8924 (V/TTY). If you have a letter from DSS indicating that you have a disability which requires academic accommodations, please present the letter to me so we can discuss the accommodations you might need in the class.

Academic accommodations due to disability will not be made unless the student has a letter from DSS specifying the type and nature of accommodations needed.

Grading Criteria

General grading information for the University of Washington is available at:

http://www.washington.edu/students/gencat/front/Grading_Sys.html

The iSchool has adopted its own criteria for grading graduate courses. The grading criteria used by the iSchool is available at: http://www.ischool.washington.edu/resources/academic/grading.aspx

The UW undergraduate grading guidelines, used by the iSchool and available at http://depts.washington.edu/grading/practices/guidelin.htm, may be used in this class.

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The following paragraphs discussing matters governing academic conduct in the iSchool and the University of Washington.

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The essence of academic life revolves around respect not only for the ideas of others, but also their rights to those ideas and their promulgation. It is therefore essential that all of us engaged in the life of the mind take the utmost care that the ideas and expressions of ideas of other people always be appropriately handled, and, where necessary, cited. For writing assignments, when ideas or materials of others are used, they must be cited. The format is not that important–as long as the source material can be located and the citation verified, it’s OK. What is important is that the material be cited. In any situation, if you have a question, please feel free to ask. Such attention to ideas and acknowledgment of their sources is central not only to academic life, but life in general.

Please acquaint yourself with the University of Washington's resources on academic honesty (http://depts.washington.edu/grading/issue1/honesty.htm).

Students are encouraged to take drafts of their writing assignments to the Writing Center for assistance with using citations ethically and effectively. Information on scheduling an appointment can be found at: http://depts.washington.edu/iwrite/

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Knowing violations of these principles of academic conduct, privacy or copyright may result in University disciplinary action under the Student Code of Conduct.

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Good student conduct is important for maintaining a healthy course environment. Please familiarize yourself with the University of Washington's Student Code of Conduct at:
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Evaluation of Student Work:

You may expect to receive comments on and evaluations of assignments and submitted work in a timely fashion. All work from the course will be returned, with comments, within two weeks of the last class of the quarter.