Information Retrieval & Web Search

CS 242: Information Retrieval & Web Search

Winter 2024

General Info

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Lecture time: M 5:00-6:20 pm, W 5:30-6:50 pm

Location: Room A125

Office hour: Wednesday 4:30-5:30 pm (WCH 317)

TAs:
Shihab Rashid
Meem

Office hours:
Shihab: Wednesdays 1:00 - 2:00 PM, WCH 363
Meem, Thursdays 1:00-2:00 pm, WCH 363

Reader: Pooja Patil

Grading

25% 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 deep learning and 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, deep learning in IR

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 8	Class Overview, Overview of Information Retrieval and Search Engines	Ch. 1, 2 slides Ch. 1 and 2
Jan 10, 17	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 22	Hands-on Scrapy and Lucene (by TA)	Slides
Jan 24, 29	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 31, Feb 5	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 7, 12	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 14	Hands-on BERT with PyTorch and Faiss (by TA)	slides	https://github.com/facebookresearch/faiss/wiki/Getting-started
Feb 21	Evaluation	Ch. 8, slides Ch. 8-short	(p3) R. Fagin, Ravi Kumar and D.Sivakumar: Comparing top-k lists. SIAM J. Discrete Mathematics 17, 1 (2003)
Feb 26	Review session	slides
Feb 28	MIDTERM
Mar 4 , 6	Deep learning and IR	Deep Learning in IR	Lin, Jimmy, Rodrigo Nogueira, and Andrew Yates. "Pretrained transformers for text ranking: Bert and beyond." Synthesis Lectures on Human Language Technologies 14, no. 4 (2021): 1-325. Ouyang, Long, Jeff Wu, Xu Jiang, Diogo Almeida, Carroll L. Wainwright, Pamela Mishkin, Chong Zhang et al. "Training language models to follow instructions with human feedback." arXiv preprint arXiv:2203.02155 (2022).
Mar 11	no class
Mar 13	Project Presentations 5-7:00 pm at SSC 229
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.
	Text Processing, Query Refinement, Results Presentation (snippets), Social Search, Question Answering, web search advertising (if time)	Ch. 4.1, 4.2, 4.3, slides Ch. 4, Ch. 6.1, 6.2, 63, slides Ch. 6 Ch 10, slides Ch. 10	G. Salton, C Buckley. Improving retrieval performance by relevance feedback. Journal of the American Society for Information Science, 1990 Tomas Mikolov, Kai Chen, Greg Corrado, and Jeﬀrey Dean. Eﬃcient estimation 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 compositionality. 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.