Information Retrieval & Web Search

CS 242: Information Retrieval & Web Search

Winter 2021

Announcements

Midterm is open notes and taken on iLearn
Welcome to the CS 242 web page!

General Info

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Lecture time: T/Th 2-3:20 pm

Location: Zoom

Office hour: Wednesday 4-5 pm

TA:
Luxun Xu
Office hour: Monday 1pm to 2pm

Reader:
Huayue Gu

Grading

25% participation and quizzes (worst 2 quizzes will be discarded, MSOL students will have until the weekend to take the quiz; others will take the quiz during the lecture time)

25% midterm

15% assignment

35% project

Course Description

Information Retrieval (IR) principles including indexing and searching document collections, Web search and advanced topics like search in social networks.

Some of the topics which will be tentatively presented are:

Vector Model
Language Models
IR evaluation methods
Web search
MapReduce
Social networks search
Word embeddings

Assignment

assignment

Project

project

Late submissions, submitted before assignments or projects are graded, will receive a 20% score reduction.

Tentative Lectures' Schedule

Date	Topic	Book Chapters	supplemental material for further reading
Jan 7	Class Overview, Overview of Information Retrieval and Search Engines	Ch. 1, 2 slides Ch. 1, slides Ch. 2 (slightly more detailed version of slides of Ch. 1)
Jan 12, 14	Ranking: Vector space model, Probabilistic Model, Language model	Ch 7.1, 7.2, 7.3 (except 7.3.2) slides Ch. 7	Yunbo Cao, Jun Xu, Tie-Yan Liu, Hang Li, Yalou Huang, Hsiao-Wuen Hon. Adapting Ranking SVM to Document Retrieval. In Proceedings of the 29th Annual International ACM SIGIR Conference (SIGIR'06), pages 186-193, 2006. (pdf)
Jan 19, 21	Crawling, Storing	Ch. 3, slides Ch. 3	(p1) Heydon, A. and Najork, M. 1999.Mercator: A scalable, extensible Web crawler. World Wide Web 2, 4 (Apr. 1999), 219-229. (slides)
Jan 26, 28	Indexing, MapReduce, Query Processing	Ch. 5 (except 5.4.2-5.4.7, 5.7.4-5.7.5), slides Ch. 5	(p2) R. Fagin, Amnon Lotem and Moni Naor. Optimal aggregation algorithms for middleware J. Computer and System Sciences 66 (2003), pp. 614-656. Extended abstract appeared in Proc. 2001 ACM Symposium on Principles of Database Systems (PODS '01), pp. 102-113 (p6) Jeffrey Dean and Sanjay Ghemawat.MapReduce: simplified data processing on large clusters. OSDI 2004
Feb 2	Set up and use Hadoop and Lucene (by TA)	Slides Hadoop example Set up single node Hadoop cluster Run and debug Hadoop program with Intellij and Maven bitnami: VM Image with Hadoop
Feb 4, 9	Link Analysis	Ch. 4.5 slides: link-based search	(p4) L. Page, S. Brin, R. Motwani, T.Winograd. The PageRank Citation Ranking: Bringing Order to the Web. 1999 (p5) J. Kleinberg. Authoritative sources in a hyperlinked environment. Journal of the ACM 46(1999).
Feb 11	Evaluation Part 1	Ch. 8, slides Ch. 8	(p3) R. Fagin, Ravi Kumar and D.Sivakumar: Comparing top-k lists. SIAM J. Discrete Mathematics 17, 1 (2003)
Feb 16	Review session	slides
Feb 18	MIDTERM on iLearn
Feb 23	Evaluation Part 2	Ch. 8 (cont'd), slides Ch. 8
Feb 25	Text Processing	Ch. 4.1, 4.2, 4.3, slides Ch. 4
Mar 2,4	Query Refinement, Results Presentation (snippets), word2vec, web search advertising (if time)	Ch. 6.1, 6.2, 63, slides Ch. 6, word embeddings	G Salton, C Buckley. Improving retrieval performance by relevance feedback. Journal of the American Society for Information Science, 1990 Zamir, O. and Etzioni, O. 1998.Web document clustering: a feasibility demonstration. ACM SIGIR '98 Tomas Mikolov, Kai Chen, Greg Corrado, and Jeﬀrey Dean. Eﬃcient es- timation of word representations in vector space. CoRR, abs/1301.3781, 2013. Tomas Mikolov, Ilya Sutskever, Kai Chen, Gregory S. Corrado, and Jeﬀrey Dean. Distributed representations of words and phrases and their composi- tionality. In Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Pro- ceedings of a meeting held December 5-8, 2013, Lake Tahoe, Nevada, United States, pages 3111�3119, 2013.
Mar 9	Social Search, Question Answering Systems	Ch 10, slides Ch. 10	(p11) Eric Brill, Susan Dumais, MicheleBanko An Analysis of the AskMSRQuestion-Answering System (EMNLP2002) (p9) Paul Heymann, Georgia Koutrika, and Hector Garcia-Molina. 2008. Can social bookmarking improve web search?. In Proceedings of the international conference on Web search and web data mining (WSDM '08) (p10) David Carmel, Naama Zwerdling, Ido Guy, Shila Ofek-Koifman, Nadav Har'el, Inbal Ronen, Erel Uziel, Sivan Yogev, and Sergey Chernov. 2009. Personalized social search based on the user's social network. In Proceeding of the 18th ACM conference on Information and knowledge management (CIKM '09)
Mar 11	Project Presentations
Interesting topics but no time to present in class	Ad words	online advertising (ASU slides)
	Relational DB and XML Search	1. IR and DB	(p13) Sara Cohen, Jonathan Mamou,Yaron Kanza, Yehoshua Sagiv: XSEarch: A Semantic Search Engine for XML. 45-56, VLDB 2004 (p14) L. Guo, F. Shao, C. Botev, J.Shanmugasundaram: XRANK: Ranked Keyword Search over XML Documents. SIGMOD 2003
	Web Search: Spam, topic-specific pagerank	1. text classification 2. Alexandros Ntoulas, Marc Najork, Mark Manasse, and Dennis Fetterly. 2006. Detecting spam web pages through content analysis. In Proceedings of the 15th international conference on World Wide Web (WWW '06) 3. Taher H. Haveliwala, "Topic-Sensitive PageRank: A Context-Sensitive Ranking Algorithm for Web Search," IEEE Transactions on Knowledge and Data Engineering, vol. 15, no. 4, pp. 784-796, Jul/Aug, 2003.