WeekLectureLabCourseworkReadings11 - IntroductionLab 0-IR in Practice Chapters 1 & 22 - Definitions23 - LawsLab 1-Intro to IR Chapter 2 --> 2.2.4 IR in Practice Chapter 4 Zipf’s law, Vsouce Benford’s law, Numberphile4 - Preprocessing35 - IndexingLab 2-Intro to IR Chapters 1, 2.4 and 3.1-3.4 IR in Practice chapter 56 - Indexing 247 - Ranked RetrievalLab 3CW1 slidesIntro to IR Chapters 6.2 to 6.4 and 12IR in Practice Chapter 7Robertson, Stephen E., et al. "Okapi at TREC-3."J. Ponte and W. B. Croft. "A language modeling approach to information retrieval."8 - Ranked Retrieval 259 - Evaluation- Intro to IR Chapters 8IR in Practice Chapter 8C Buckley and E. M. Voorhees. "Retrieval Evaluation with Incomplete Information."10 - Evaluation 2611 - QELab 5 Intro to IR Chapters 9IR in Practice Chapter 6.2, 6.3Magdy W. and G. J. F. Jones. A Study on Query Expansion Methods for Patent Retrieval12 - Applications713 - Web Search- Intro to IR Chapters 19, 21.1IR in Practice Chapter 3, 4.5, 10.3Page, L., Brin, S., Motwani, R., & Winograd, T. (1999). The PageRank citation ranking: Bringing order to the web.14 - Web Search 2815 - Comparing CorporaLab 6CW2 instructionsIntro to IR Chapters 13.5“Probabilistic Topic Models” by David Blei“Latent Dirichlet Allocation” by David Blei, Andrew Y. Ng, and Michael I. Jordan“Probabilistic Topic Models” by Mark Steyvers and TomGriffithsTo watch: Guest lecture (2017) by David Blei at University of Edinburgh School of Informatics16 - Comparing Corpora 2 9No lecture on 15 November 20231017 - Text ClassificationLab 7CW2 slides"Machine Learning in Automated Text Categorization" by Fabrizio Sebastiani"A Primer on Neural Network Models for NaturalLanguage Processing" by Yoav Goldberg"Bridging Social Media via Distant Supervision" by Walid Magdy et al.Text Classification pages on Huggingface.co18 - Text Classification 2Jupyter notebook1119 - Learning to Rank CW3 slidesNallapati, Ramesh. Discriminative models for information retrieval. SIGIR 2004.Burges, C. J. (2010). From ranknet to lambdarank to lambdamart: An overview. Learning, 11(23-581), 81.SVMRank: http://svmlight.joachims.org/L2R test sets:Microsoft’s LETOR projecthttp://research.microsoft.com/en-us/um/beijing/projects/letor//default.aspx License All rights reserved The University of Edinburgh Book traversal links for TTDS: Schedule TTDS: Course Materials Up TTDS: Labs