{"id":213,"date":"2021-08-02T19:28:20","date_gmt":"2021-08-03T00:28:20","guid":{"rendered":"https:\/\/groups.cs.umass.edu\/zamani\/?page_id=213"},"modified":"2022-01-15T16:38:55","modified_gmt":"2022-01-15T21:38:55","slug":"compsci-646-information-retrieval-fall-2021","status":"publish","type":"page","link":"https:\/\/groups.cs.umass.edu\/zamani\/compsci-646-information-retrieval-fall-2021\/","title":{"rendered":"COMPSCI 646: Information Retrieval &#8211; Fall 2021"},"content":{"rendered":"\n<p>COMPSCI 646 is a graduate-level course in Information Retrieval, the science and engineering of indexing, organizing, searching, and making sense of unstructured or mostly unstructured information, particularly text. The class focuses primarily on the underlying models used for effective search and organization, but includes some discussion of efficiency concerns. The course also covers current research problems and methodologies in the field of Information Retrieval.<\/p>\n<p><a href=\"https:\/\/groups.cs.umass.edu\/zamani\/wp-content\/uploads\/sites\/41\/2021\/08\/time-icon.png\"><img decoding=\"async\" class=\"alignnone wp-image-254\" src=\"https:\/\/groups.cs.umass.edu\/zamani\/wp-content\/uploads\/sites\/41\/2021\/08\/time-icon-150x150.png\" alt=\"\" width=\"45\" height=\"45\" srcset=\"https:\/\/groups.cs.umass.edu\/zamani\/wp-content\/uploads\/sites\/41\/2021\/08\/time-icon-150x150.png 150w, https:\/\/groups.cs.umass.edu\/zamani\/wp-content\/uploads\/sites\/41\/2021\/08\/time-icon.png 225w\" sizes=\"(max-width: 45px) 100vw, 45px\" \/><\/a>Tue &amp; Thu, 4:00 &#8211; 5:15 PM<\/p>\n<p><a href=\"https:\/\/groups.cs.umass.edu\/zamani\/wp-content\/uploads\/sites\/41\/2021\/08\/location-icon.png\"><img decoding=\"async\" class=\"alignnone wp-image-258\" src=\"https:\/\/groups.cs.umass.edu\/zamani\/wp-content\/uploads\/sites\/41\/2021\/08\/location-icon-150x150.png\" alt=\"\" width=\"45\" height=\"45\" srcset=\"https:\/\/groups.cs.umass.edu\/zamani\/wp-content\/uploads\/sites\/41\/2021\/08\/location-icon-150x150.png 150w, https:\/\/groups.cs.umass.edu\/zamani\/wp-content\/uploads\/sites\/41\/2021\/08\/location-icon-300x300.png 300w, https:\/\/groups.cs.umass.edu\/zamani\/wp-content\/uploads\/sites\/41\/2021\/08\/location-icon.png 512w\" sizes=\"(max-width: 45px) 100vw, 45px\" \/><\/a>CS 142<\/p>\n<hr \/>\n<table style=\"width: 100%;border-collapse: collapse;border-style: none\">\n<tbody>\n<tr>\n<td style=\"width: 30.2381%;border-style: none\"><a href=\"https:\/\/groups.cs.umass.edu\/zamani\/wp-content\/uploads\/sites\/41\/2021\/07\/zamani-photo-2-1.png\"><img decoding=\"async\" class=\"alignnone wp-image-78 size-thumbnail\" src=\"https:\/\/groups.cs.umass.edu\/zamani\/wp-content\/uploads\/sites\/41\/2021\/07\/zamani-photo-2-1-150x150.png\" alt=\"Hamed Zamani - UMass Amherst\" width=\"150\" height=\"150\" srcset=\"https:\/\/groups.cs.umass.edu\/zamani\/wp-content\/uploads\/sites\/41\/2021\/07\/zamani-photo-2-1-150x150.png 150w, https:\/\/groups.cs.umass.edu\/zamani\/wp-content\/uploads\/sites\/41\/2021\/07\/zamani-photo-2-1-300x297.png 300w, https:\/\/groups.cs.umass.edu\/zamani\/wp-content\/uploads\/sites\/41\/2021\/07\/zamani-photo-2-1.png 404w\" sizes=\"(max-width: 150px) 100vw, 150px\" \/><\/a><\/td>\n<td style=\"width: 69.7619%;border-style: none\">\n<p><strong>Instructor:<\/strong><br \/>Hamed Zamani<br \/>Contact: zamani@cs.umass.edu<br \/>Office Hours: Tue &amp; Thu, 9:00 &#8211; 10:00 AM @ CS 350<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td style=\"width: 30.2381%;border-style: none\"><a href=\"https:\/\/groups.cs.umass.edu\/zamani\/wp-content\/uploads\/sites\/41\/2018\/10\/blog-portrait.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-5\" src=\"https:\/\/groups.cs.umass.edu\/zamani\/wp-content\/uploads\/sites\/41\/2018\/10\/blog-portrait.jpg\" alt=\"\" width=\"150\" height=\"150\" \/><\/a><\/td>\n<td style=\"width: 69.7619%;border-style: none\"><strong>Teaching Assistant:<\/strong><br \/>Lakshmi Vikraman<br \/>Contact: lvnair@cs.umass.edu<br \/>Office Hours: Mon &amp; Wed, 10:00 &#8211; 11:00 AM @ LGRT 220 (T220)<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<hr \/>\n<h2>Prerequisites<\/h2>\n<ul>\n<li>Proficiency in Python and\/or Java<\/li>\n<li>Basic knowledge of probability, statistics, and information theory<\/li>\n<li>Foundations of applied machine learning and deep learning<\/li>\n<\/ul>\n<h2><br \/>Textbook<\/h2>\n<ul>\n<li><b>[WBC]<\/b>\u00a0W. Bruce Croft, Donald Metzler, and Trevor Strohman.\u00a0<a href=\"http:\/\/ciir.cs.umass.edu\/irbook\/\">Search Engines: Information Retrieval in Practice<\/a>. Pearson Education, 2009.<\/li>\n<li><b>[CDM]<\/b>\u00a0Christopher D. Manning, Prabhakar Raghavan, and Hinrich Sch\u00fctze.\u00a0<a href=\"http:\/\/nlp.stanford.edu\/IR-book\/\">Introduction to Information Retrieval<\/a>. Cambridge University Press, 2008.<\/li>\n<\/ul>\n<h2><br \/>Grading<\/h2>\n<ul>\n<li>Assignments (3&#215;10%)<\/li>\n<li>Midterm exam (25%): <strong>Friday, October 29, 2021, 7 &#8211; 9 PM<\/strong><\/li>\n<li>Final exam, take home (20%)<\/li>\n<li>Final project (25%)<\/li>\n<\/ul>\n<h2><br \/>Tentative Schedule<\/h2>\n<table style=\"width: 100.117%;height: 3666px\">\n<tbody>\n<tr style=\"height: 24px\">\n<td style=\"width: 5.15789%;height: 24px\" width=\"50px\">#<\/td>\n<td style=\"width: 23.4154%;height: 24px\" width=\"300px\">Lecture<\/td>\n<td style=\"width: 9.58876%;height: 24px\" width=\"100px\">Date<\/td>\n<td style=\"width: 49.031%;height: 24px\" width=\"500px\">Readings<\/td>\n<\/tr>\n<tr style=\"height: 66px\">\n<td style=\"width: 5.15789%;height: 66px\">1<\/td>\n<td style=\"width: 23.4154%;height: 66px\">Introduction<\/td>\n<td style=\"width: 9.58876%;height: 66px\">Thu 9\/2<\/td>\n<td style=\"width: 49.031%;height: 132px\" rowspan=\"2\">\n<ul>\n<li>[WBC] Ch.1<\/li>\n<li>[WBC] Ch.7.1<\/li>\n<li>[CDM] Ch.8.1, 8.2<\/li>\n<\/ul>\n<\/td>\n<\/tr>\n<tr style=\"height: 66px\">\n<td style=\"width: 5.15789%;height: 66px\">2<\/td>\n<td style=\"width: 23.4154%;height: 66px\">IR Basics<\/td>\n<td style=\"width: 9.58876%;height: 66px\">Tue 9\/7<\/td>\n<\/tr>\n<tr style=\"height: 105px\">\n<td style=\"width: 5.15789%;height: 105px\">3<\/td>\n<td style=\"width: 23.4154%;height: 210px\" rowspan=\"2\">IR Evaluation Methodologies, Metrics, and User Models<\/td>\n<td style=\"width: 9.58876%;height: 105px\">Thu 9\/9<\/td>\n<td style=\"width: 49.031%;height: 210px\" rowspan=\"2\">\n<ul>\n<li>[CDM] Ch.8.3, 8.4<\/li>\n<li>(optional) NDCG:\u00a0<a href=\"https:\/\/dl.acm.org\/citation.cfm?id=582418\" target=\"\\blank\" rel=\"noopener\">J\u00e4rvelin and Kek\u00e4l\u00e4inen (TOIS 2002)<\/a><\/li>\n<\/ul>\n<\/td>\n<\/tr>\n<tr style=\"height: 105px\">\n<td style=\"width: 5.15789%;height: 105px\">4<\/td>\n<td style=\"width: 9.58876%;height: 105px\">Tue 9\/14<\/td>\n<\/tr>\n<tr style=\"height: 66px\">\n<td style=\"width: 5.15789%;height: 66px\">5<\/td>\n<td style=\"width: 23.4154%;height: 66px\">Text Processing and Indexing<\/td>\n<td style=\"width: 9.58876%;height: 66px\">Thu 9\/16<\/td>\n<td style=\"height: 66px;width: 49.031%\">\n<ul>\n<li>[WBC] Ch.4.1, 4.2, 4.3<\/li>\n<li>[WBC] Ch.5.1, 5.2, 5.3, 5.4, 5.7<\/li>\n<\/ul>\n<\/td>\n<\/tr>\n<tr style=\"height: 66px\">\n<td style=\"width: 5.15789%;height: 66px\">6<\/td>\n<td style=\"width: 23.4154%;height: 66px\">Basic Retrieval Models: Vector Space Models &amp; Probabilistic Retrieval Models<\/td>\n<td style=\"width: 9.58876%;height: 66px\">Tue 9\/21<\/td>\n<td style=\"width: 49.031%;height: 66px\">\n<ul>\n<li>[CDM] Ch.6.2, 6.3, 6.4<\/li>\n<li>[CDM] Ch.11.1, 11.2, 11.3, 11.4.3<\/li>\n<\/ul>\n<\/td>\n<\/tr>\n<tr style=\"height: 76px\">\n<td style=\"width: 5.15789%;height: 76px\">7<\/td>\n<td style=\"width: 23.4154%;height: 219px\">Language Modeling<\/td>\n<td style=\"width: 9.58876%;height: 76px\">Thu 9\/23<\/td>\n<td style=\"width: 49.031%;height: 219px\">\n<ul>\n<li>[CDM] Ch.12.1, 12.2, 12.3<\/li>\n<li>(optional) Query likelihood:\u00a0<a href=\"https:\/\/dl.acm.org\/citation.cfm?id=291008\" target=\"\\blank\" rel=\"noopener\">Ponte and Croft (SIGIR 1998)<\/a><\/li>\n<li>(optional) KL-divergence retrieval model:\u00a0<a href=\"https:\/\/dl.acm.org\/citation.cfm?id=383970\" target=\"\\blank\" rel=\"noopener\">Lafferty and Zhai (SIGIR 2001)<\/a><\/li>\n<li>(optional) Language model smoothing:\u00a0<a href=\"https:\/\/dl.acm.org\/citation.cfm?id=984322\" target=\"\\blank\" rel=\"noopener\">Zhai and Lafferty (TOIS 2004)<\/a><\/li>\n<\/ul>\n<\/td>\n<\/tr>\n<tr style=\"height: 219px\">\n<td style=\"width: 5.15789%;height: 219px\">8<\/td>\n<td style=\"width: 23.4154%;height: 362px\">Enhanced Language Modeling<\/td>\n<td style=\"width: 9.58876%;height: 219px\">Tue 9\/28<\/td>\n<td style=\"width: 49.031%;height: 362px\">\n<ul>\n<li>[WBC] Ch.11.3<\/li>\n<li>[CDM] Ch.12.4<\/li>\n<li>(optional) Cluster-based LM:\u00a0<a href=\"https:\/\/dl.acm.org\/citation.cfm?id=1009026\" target=\"\\blank\" rel=\"noopener\">Liu and Croft (SIGIR 2004)<\/a><\/li>\n<li>(optional) LDA-based LM:\u00a0<a href=\"https:\/\/dl.acm.org\/citation.cfm?id=1148204\" target=\"\\blank\" rel=\"noopener\">Wei and Croft (SIGIR 2006)<\/a><\/li>\n<li>(optional) Local document expansion:\u00a0<a href=\"https:\/\/www.aclweb.org\/anthology\/N\/N06\/N06-1052.pdf\" target=\"\\blank\" rel=\"noopener\">Tao et al. (NAACL 2006)<\/a><\/li>\n<li>(optional) General LM:\u00a0<a href=\"https:\/\/dl.acm.org\/citation.cfm?id=320022\" target=\"\\blank\" rel=\"noopener\">Song and Croft (CIKM 1999)<\/a><\/li>\n<li>(optional) HMM IR:\u00a0<a href=\"https:\/\/dl.acm.org\/citation.cfm?id=312680\" target=\"\\blank\" rel=\"noopener\">Miller et al. (SIGIR 1999)<\/a><\/li>\n<li>(optional) Dependence models:\u00a0<a href=\"https:\/\/dl.acm.org\/citation.cfm?id=1076115\" target=\"\\blank\" rel=\"noopener\">Metzler and Croft (SIGIR 2005)<\/a><\/li>\n<li>(optional) Positional LM:\u00a0<a href=\"https:\/\/dl.acm.org\/citation.cfm?id=1571994\" target=\"\\blank\" rel=\"noopener\">Lv and Zhai (SIGIR 2009)<\/a><\/li>\n<\/ul>\n<\/td>\n<\/tr>\n<tr style=\"height: 362px\">\n<td style=\"width: 5.15789%;height: 362px\">9<\/td>\n<td style=\"width: 23.4154%;height: 247px\">Relevance Feedback<\/td>\n<td style=\"width: 9.58876%;height: 362px\">Thu 9\/30<\/td>\n<td style=\"width: 49.031%;height: 247px\">\n<ul>\n<li>[WBC] Ch.7.3.2<\/li>\n<li>(optional) Relevance models:\u00a0<a href=\"https:\/\/dl.acm.org\/citation.cfm?id=3130376\" target=\"\\blank\" rel=\"noopener\">Lavrenko and Croft (SIGIR 2001)<\/a><\/li>\n<li>(optional) Model-based feedback:\u00a0<a href=\"https:\/\/dl.acm.org\/citation.cfm?id=502654\" target=\"\\blank\" rel=\"noopener\">Zhai and Lafferty (CIKM 2001)<\/a><\/li>\n<li>(optional) Matrix factorization model:\u00a0<a href=\"https:\/\/dl.acm.org\/citation.cfm?id=2983844\" target=\"\\blank\" rel=\"noopener\">Zamani et al. (CIKM 2016)<\/a><\/li>\n<\/ul>\n<\/td>\n<\/tr>\n<tr style=\"height: 247px\">\n<td style=\"width: 5.15789%;height: 247px\">10<\/td>\n<td style=\"width: 23.4154%;height: 105px\">ML Basics &amp; Learning to Rank<\/td>\n<td style=\"width: 9.58876%;height: 247px\">Tue. 10\/5<\/td>\n<td style=\"width: 49.031%;height: 105px\">\n<ul>\n<li>LTR Textbook:\u00a0<a href=\"https:\/\/www.morganclaypool.com\/doi\/abs\/10.2200\/S00348ED1V01Y201104HLT012\" target=\"\\blank\" rel=\"noopener\">Li (2011)<\/a>\u00a0Ch.1, 2, 6<\/li>\n<li>(optional) LTR Textbook:\u00a0<a href=\"https:\/\/www.morganclaypool.com\/doi\/abs\/10.2200\/S00348ED1V01Y201104HLT012\" target=\"\\blank\" rel=\"noopener\">Li (2011)<\/a>\u00a0Ch.4<\/li>\n<\/ul>\n<\/td>\n<\/tr>\n<tr style=\"height: 105px\">\n<td style=\"width: 5.15789%;height: 105px\">11<\/td>\n<td style=\"width: 23.4154%;height: 219px\">Introduction to Neural Networks and Neural IR<\/td>\n<td style=\"width: 9.58876%;height: 105px\">Thu 10\/7<\/td>\n<td style=\"width: 49.031%;height: 219px\">\u00a0<\/td>\n<\/tr>\n<tr style=\"height: 219px\">\n<td style=\"width: 5.15789%;height: 219px\">12<\/td>\n<td style=\"width: 23.4154%;height: 162px\">\n<p>Distributed Representation Learning for Text<\/p>\n<\/td>\n<td style=\"width: 9.58876%;height: 219px\">Tue 10\/12<\/td>\n<td style=\"width: 49.031%;height: 162px\">\n<ul>\n<li>word2vec:\u00a0<a href=\"http:\/\/papers.nips.cc\/paper\/5021-distributed-representations-of-words-andphrases\" target=\"\\blank\" rel=\"noopener\">Mikolov et al. (NIPS 2013)<\/a><\/li>\n<li>(optional) GloVe:\u00a0<a href=\"https:\/\/nlp.stanford.edu\/pubs\/glove.pdf\" target=\"\\blank\" rel=\"noopener\">Pennington et al. (EMNLP 2014)<\/a><\/li>\n<li>(optional) Relevance-based Word Embedding:\u00a0<a href=\"http:\/\/doi.acm.org\/10.1145\/3077136.3080831\" target=\"\\blank\" rel=\"noopener\">Zamani and Croft (SIGIR 2017)<\/a><\/li>\n<li>(optional) Embedding-based Query Expansion:\u00a0<a href=\"http:\/\/doi.acm.org\/10.1145\/2970398.2970405\" target=\"\\blank\" rel=\"noopener\">Zamani and Croft (ICTIR 2016)<\/a><\/li>\n<\/ul>\n<\/td>\n<\/tr>\n<tr style=\"height: 162px\">\n<td style=\"width: 5.15789%;height: 162px\">13<\/td>\n<td style=\"width: 23.4154%;height: 162px\" rowspan=\"2\">Neural Ranking Models<\/td>\n<td style=\"width: 9.58876%;height: 162px\">Thu 10\/14<\/td>\n<td style=\"width: 49.031%;height: 162px\" rowspan=\"2\">\n<ul>\n<li>(optional) DSSM:\u00a0<a href=\"https:\/\/dl.acm.org\/citation.cfm?id=2505665\" target=\"\\blank\" rel=\"noopener\">Huang et al. (CIKM 2013)<\/a><\/li>\n<li>(optional) K-NRM:\u00a0<a href=\"https:\/\/dl.acm.org\/citation.cfm?id=3080809\" target=\"\\blank\" rel=\"noopener\">Xiong et al. (SIGIR 2017)<\/a><\/li>\n<li>(optional) Duet Model:\u00a0<a href=\"https:\/\/dl.acm.org\/citation.cfm?id=3052579\" target=\"\\blank\" rel=\"noopener\">Mitra et al. (WWW 2017)<\/a><\/li>\n<li>(optional) SNRM:\u00a0<a href=\"https:\/\/dl.acm.org\/citation.cfm?id=3271800\" target=\"\\blank\" rel=\"noopener\">Zamani et al. (CIKM 2018)<\/a><\/li>\n<\/ul>\n<\/td>\n<\/tr>\n<tr style=\"height: 219px\">\n<td style=\"width: 5.15789%;height: 219px\">14<\/td>\n<td style=\"width: 9.58876%;height: 219px\">Tue 10\/19<\/td>\n<\/tr>\n<tr style=\"height: 247px\">\n<td style=\"width: 5.15789%;height: 247px\">15<\/td>\n<td style=\"width: 23.4154%;height: 190px\">Implicit Feedback, Biases, and Click Models<\/td>\n<td style=\"width: 9.58876%;height: 247px\">Thu 10\/21<\/td>\n<td style=\"width: 49.031%;height: 190px\">\n<ul>\n<li>(optional) Implicit feedback:\u00a0<a href=\"https:\/\/dl.acm.org\/citation.cfm?id=1076063\" target=\"\\blank\" rel=\"noopener\">Joachims et al. (SIGIR 2005)<\/a><\/li>\n<li>(optional) Click models for web search:\u00a0<a href=\"https:\/\/www.morganclaypool.com\/doi\/abs\/10.2200\/S00654ED1V01Y201507ICR043\" target=\"\\blank\" rel=\"noopener\">Chuklin et al. (2015)<\/a><\/li>\n<li>(optional) Counterfactual learning:\u00a0<a href=\"http:\/\/www.cs.cornell.edu\/~adith\/CfactSIGIR2016\/\" target=\"\\blank\" rel=\"noopener\">Joachims and Swaminathan (SIGIR 2016)<\/a><\/li>\n<li>(optional) Unbiased learning to rank:\u00a0<a href=\"https:\/\/dl.acm.org\/citation.cfm?id=3018699\" target=\"\\blank\" rel=\"noopener\">Joachims et al. (WSDM 2017)<\/a><\/li>\n<\/ul>\n<\/td>\n<\/tr>\n<tr style=\"height: 190px\">\n<td style=\"width: 5.15789%;height: 190px\">16<\/td>\n<td style=\"width: 23.4154%;height: 162px\">Web Search: Link Analysis, Spam Filtering, MapReduce<\/td>\n<td style=\"width: 9.58876%;height: 190px\">Tue 10\/26<\/td>\n<td style=\"width: 49.031%;height: 162px\">\n<ul>\n<li>[CDM] Ch.21<\/li>\n<li>(optional) PageRank:\u00a0<a href=\"http:\/\/ilpubs.stanford.edu:8090\/422\/1\/1999-66.pdf\" target=\"\\blank\" rel=\"noopener\">Page et al. (1998)<\/a><\/li>\n<li>(optional) HITS:\u00a0<a href=\"https:\/\/dl.acm.org\/citation.cfm?id=324140\" target=\"\\blank\" rel=\"noopener\">Kleinberg (JACM 1999)<\/a><\/li>\n<li>(optional) Waterloo spam scorer:\u00a0<a href=\"https:\/\/link.springer.com\/article\/10.1007\/s10791-011-9162-z\" target=\"\\blank\" rel=\"noopener\">Cormack et al. (IRJ 2011)<\/a><\/li>\n<\/ul>\n<\/td>\n<\/tr>\n<tr style=\"height: 162px\">\n<td style=\"width: 5.15789%;height: 162px\">17<\/td>\n<td style=\"width: 23.4154%;height: 45px\">Context-Awareness and Personalization in Search<\/td>\n<td style=\"width: 9.58876%;height: 162px\">Thu 10\/28<\/td>\n<td style=\"width: 49.031%;height: 45px\">\n<ul>\n<li>(optional) Context-sensitive language model:\u00a0<a href=\"https:\/\/dl.acm.org\/citation.cfm?id=1076045\" target=\"\\blank\" rel=\"noopener\">Shen et al. (SIGIR 2005)<\/a><\/li>\n<li>(optional) Web search personalization:\u00a0<a href=\"https:\/\/dl.acm.org\/citation.cfm?id=2348312\" target=\"\\blank\" rel=\"noopener\">Bennett et al. (SIGIR 2012)<\/a><\/li>\n<li>(optional) Situational context for search:\u00a0<a href=\"https:\/\/dl.acm.org\/citation.cfm?doid=3038912.3052648\" target=\"\\blank\" rel=\"noopener\">Zamani et al. (WWW 2017)<\/a><\/li>\n<\/ul>\n<\/td>\n<\/tr>\n<tr style=\"height: 45px\">\n<td style=\"width: 5.15789%;height: 45px\">18<\/td>\n<td style=\"width: 23.4154%;height: 219px\">Novelty and Diversity<\/td>\n<td style=\"width: 9.58876%;height: 45px\">Tue 11\/2<\/td>\n<td style=\"width: 49.031%;height: 219px\">\n<ul>\n<li>Maximal Marginal Relevance (MMR):\u00a0<a href=\"https:\/\/dl.acm.org\/citation.cfm?id=291025\" target=\"\\blank\" rel=\"noopener\">Carbonell and Goldstein (SIGIR 1998)<\/a><\/li>\n<li>Novelty and diversity evaluation:\u00a0<a href=\"https:\/\/dl.acm.org\/citation.cfm?id=1390446\" target=\"\\blank\" rel=\"noopener\">Clarke et al. (SIGIR 2008)<\/a><\/li>\n<li>(optional) Subtopic retrieval using language models:\u00a0<a href=\"https:\/\/dl.acm.org\/citation.cfm?id=860440\" target=\"\\blank\" rel=\"noopener\">Zhai et al. (SIGIR 2003)<\/a><\/li>\n<li>(optional) Term-level diversification:\u00a0<a href=\"https:\/\/dl.acm.org\/citation.cfm?id=2484095\" target=\"\\blank\" rel=\"noopener\">Dang and Croft (SIGIR 2013)<\/a><\/li>\n<\/ul>\n<\/td>\n<\/tr>\n<tr style=\"height: 219px\">\n<td style=\"width: 5.15789%;height: 219px\">19<\/td>\n<td style=\"width: 23.4154%;height: 190px\">User Study and Crowdsourcing in IR<\/td>\n<td style=\"width: 9.58876%;height: 219px\">Thu 11\/4<\/td>\n<td style=\"width: 49.031%;height: 190px\">\n<ul>\n<li>Crowdsourcing user studies with Mechanical Turk:\u00a0<a href=\"https:\/\/dl.acm.org\/citation.cfm?id=1357127\" target=\"\\blank\" rel=\"noopener\">Kittur et al. (CHI 2008)<\/a><\/li>\n<li>(optional) Interactive IR evaluation:\u00a0<a href=\"https:\/\/dl.acm.org\/citation.cfm?id=2809465\" target=\"\\blank\" rel=\"noopener\">Kelly et al. (ICTIR 2015)<\/a><\/li>\n<li>(optional) Understanding user behaviour from query logs:\u00a0<a href=\"https:\/\/link.springer.com\/chapter\/10.1007\/978-1-4939-0378-8_14\" target=\"\\blank\" rel=\"noopener\">Dumais et al. (Ways of Knowing in HCI, 2014)<\/a><\/li>\n<\/ul>\n<\/td>\n<\/tr>\n<tr style=\"height: 190px\">\n<td style=\"width: 5.15789%;height: 190px\">20<\/td>\n<td style=\"width: 23.4154%;height: 190px\">Cross- and Multi-Lingual IR<\/td>\n<td style=\"width: 9.58876%;height: 190px\">Tue 11\/9<\/td>\n<td style=\"width: 49.031%;height: 190px\">\u00a0<\/td>\n<\/tr>\n<tr style=\"height: 24px\">\n<td style=\"width: 5.15789%;height: 24px\">\u00a0<\/td>\n<td style=\"width: 23.4154%;height: 24px\"><span style=\"color: #ff0000\">No Class: Veteran&#8217;s Day<\/span><\/td>\n<td style=\"width: 9.58876%;height: 24px\">Thu 11\/11<\/td>\n<td style=\"width: 49.031%;height: 24px\">\u00a0<\/td>\n<\/tr>\n<tr style=\"height: 80px\">\n<td style=\"width: 5.15789%;height: 80px\">21<\/td>\n<td style=\"width: 23.4154%;height: 160px\" rowspan=\"2\">Information Filtering and Recommendation<\/td>\n<td style=\"width: 9.58876%;height: 80px\">Tue 11\/16<\/td>\n<td style=\"width: 49.031%;height: 160px\" rowspan=\"2\">\n<ul>\n<li>(optional) Information Retrieval and Information Filtering:\u00a0<a href=\"https:\/\/dl.acm.org\/citation.cfm?id=138861\" target=\"\\blank\" rel=\"noopener\">Belkin and Croft (CACM 1992)<\/a><\/li>\n<li>(optional) Recommender Systems Handbook:\u00a0<a href=\"https:\/\/www.springer.com\/us\/book\/9781489976369\" target=\"\\blank\" rel=\"noopener\">Ricci et al. (2015)<\/a><\/li>\n<\/ul>\n<\/td>\n<\/tr>\n<tr style=\"height: 80px\">\n<td style=\"width: 5.15789%;height: 80px\">22<\/td>\n<td style=\"width: 9.58876%;height: 80px\">Thu 11\/18<\/td>\n<\/tr>\n<tr style=\"height: 24px\">\n<td style=\"width: 5.15789%;height: 24px\">23<\/td>\n<td style=\"width: 23.4154%;height: 24px\">Entity Search<\/td>\n<td style=\"width: 9.58876%;height: 24px\">Tue 11\/23<\/td>\n<td style=\"width: 49.031%;height: 24px\">\u00a0<\/td>\n<\/tr>\n<tr style=\"height: 24px\">\n<td style=\"width: 5.15789%;height: 24px\">\u00a0<\/td>\n<td style=\"width: 23.4154%;height: 24px\"><span style=\"color: #ff0000\">No Class: Thanksgiving<\/span><\/td>\n<td style=\"width: 9.58876%;height: 24px\">Thu 11\/25<\/td>\n<td style=\"width: 49.031%;height: 24px\">\u00a0<\/td>\n<\/tr>\n<tr style=\"height: 24px\">\n<td style=\"width: 5.15789%;height: 24px\">24<\/td>\n<td style=\"width: 23.4154%;height: 24px\">Question Answering<\/td>\n<td style=\"width: 9.58876%;height: 24px\">Tue 11\/30<\/td>\n<td style=\"width: 49.031%;height: 24px\">\u00a0<\/td>\n<\/tr>\n<tr style=\"height: 88px\">\n<td style=\"width: 5.15789%;height: 88px\">25<\/td>\n<td style=\"width: 23.4154%;height: 88px\">Conversational Information Seeking<\/td>\n<td style=\"width: 9.58876%;height: 88px\">Thu 12\/2<\/td>\n<td style=\"width: 49.031%;height: 88px\">\n<p>\u00a0<\/p>\n<\/td>\n<\/tr>\n<tr style=\"height: 24px\">\n<td style=\"width: 5.15789%;height: 24px\">26<\/td>\n<td style=\"width: 23.4154%;height: 24px\">Current IR Research<\/td>\n<td style=\"width: 9.58876%;height: 24px\">Tue 12\/7<\/td>\n<td style=\"width: 49.031%;height: 24px\">\u00a0<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>\u00a0<\/h2>\n<h2>Course Policy<\/h2>\n<h3>Late Submission<\/h3>\n<p>Each student has a total of 6 late days without penalty. You can use up to 3 late days per assignment or project milestone excluding project final report. Late submission of team assignments will result in each member of the team being charged for the late days. For example, if a group of two students submitted their project proposal 23 hours after the deadline, this results in 1 late day being used per student.<br \/><br \/>Once all 6 late days are used, any assignments turned in late will be penalized 20% per late day.<br \/><br \/>In case of multiple submissions of an assignment, only the last one will be taken into account for the number of late days.<\/p>\n<h3>Collaboration and Help<\/h3>\n<p>You may discuss the ideas behind assignments with others. You may ask for help understanding class and IR concepts. You may study with friends. However&#8230;<br \/><br \/>The work that you submit must be your own. It may not be copied from the web, from another student in the class, or from anyone else. If you stumble upon and use a solution from the textbook or from class, you are expected to acknowledge the source of the work.<br \/><br \/>Your effort on exams (mini or final) must be your own. Your homework submissions must be your own work and not in collaboration with anyone. Your project work must be your own work and not a copy of someone else&#8217;s work.<\/p>\n<h3>Relevant UMass Resources<\/h3>\n<ul>\n<li><a href=\"https:\/\/www.umass.edu\/registrar\/calendars\/academic-calendar#fall2021\">UMass Academic Calendar<\/a><\/li>\n<li><a href=\"https:\/\/www.umass.edu\/honesty\/\">Academic Honesty Policy<\/a><\/li>\n<li><a href=\"https:\/\/www.umass.edu\/esl\/\">English as a Second Language (ESL) Program<\/a><\/li>\n<li><a href=\"https:\/\/www.umass.edu\/counseling\/\">Center for Counseling and Psychological Health<\/a><\/li>\n<li><a href=\"https:\/\/www.umass.edu\/disability\/\">Disability Services<\/a><\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>COMPSCI 646 is a graduate-level course in Information Retrieval, the science and engineering of indexing, organizing, searching, and making sense of unstructured or mostly unstructured information, particularly text. The class focuses primarily on the underlying models used for effective search and organization, but includes some discussion of efficiency concerns. The course also covers current research &hellip; <a href=\"https:\/\/groups.cs.umass.edu\/zamani\/compsci-646-information-retrieval-fall-2021\/\" class=\"more-link\">Continue reading<span class=\"screen-reader-text\"> &#8220;COMPSCI 646: Information Retrieval &#8211; Fall 2021&#8221;<\/span><\/a><\/p>\n","protected":false},"author":67,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-213","page","type-page","status-publish","hentry","hfeed"],"_links":{"self":[{"href":"https:\/\/groups.cs.umass.edu\/zamani\/wp-json\/wp\/v2\/pages\/213","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/groups.cs.umass.edu\/zamani\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/groups.cs.umass.edu\/zamani\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/groups.cs.umass.edu\/zamani\/wp-json\/wp\/v2\/users\/67"}],"replies":[{"embeddable":true,"href":"https:\/\/groups.cs.umass.edu\/zamani\/wp-json\/wp\/v2\/comments?post=213"}],"version-history":[{"count":50,"href":"https:\/\/groups.cs.umass.edu\/zamani\/wp-json\/wp\/v2\/pages\/213\/revisions"}],"predecessor-version":[{"id":480,"href":"https:\/\/groups.cs.umass.edu\/zamani\/wp-json\/wp\/v2\/pages\/213\/revisions\/480"}],"wp:attachment":[{"href":"https:\/\/groups.cs.umass.edu\/zamani\/wp-json\/wp\/v2\/media?parent=213"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}