CS 242: Information Retrieval & Web Search

Winter 2019


General Info

Instructor: Vagelis Hristidis

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Lecture time: M/W/F 5:10-6:00 pm

Location: MSE 003

Office hour: Friday 3-4 pm

Merlin Mao: office hour for ground (non-online) students: Tuesday 10-11 am, WCH 363

Nhat Le: lead TA for online students; Online students, please contact Nhat if you need help


Ground Students

15% participation and quizzes (worst quiz will be discarded)

40% midterm

10% assignment

35% project

Online Students

45% midterm

15% assignment

40% 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:





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


Presentations schedule:


Tentative Lectures' Schedule



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 9, 11, 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 16, 21, 23 Crawling, Storing Ch. 3, slides Ch. 3

(p1) Heydon, A. and Najork, M. 1999.Mercator: A scalable, extensible Web crawlerWorld Wide Web 2, 4 (Apr. 1999), 219-229. (slides)

Jan 25, 28, 30 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 1 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 4 Use of class Hadoop cluster and Lucene by TA slides, hadoop cluster login info, hadoop example
local Hadoop program using Intellij and Maven
Feb 6, 8

Link Analysis (cont'd)



Feb 11, 13


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 15

Review session


Feb 20 MIDTERM    
Feb 22, 25 Text Processing Ch. 4.1, 4.2, 4.3, slides Ch. 4  
Feb 27, Mar 1 Query Refinement, Results Presentation (snippets), word2vec, web search advertising (if time) Ch. 6.1, 6.2, 63, slides Ch. 6, word2vec, online advertising (ASU slides)

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,

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 4, 6

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 8 NO CLASS (instructor at workshop, work on project report)    
Mar 11, 13, 15

Project Presentations

11: Groups 1-4

13: Groups 5-8

15: Groups 9-11



Interesting topics but no time to present in class

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.


Other Resources

writing tips

presentation tips



Free download at https://ciir.cs.umass.edu/irbook/

Search Engines: Information Retrieval in Practice

Bruce Croft, Donald Metzler, Trevor Strohman

Addison Wesley; 1 edition (February 16, 2009)

ISBN-10: 0136072240

ISBN-13: 978-0136072249



Also recommended for reference:



Academic Integrity: https://conduct.ucr.edu/