• Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition by Daniel Jurafsky, James H. Martin. (J&M). We will follow the second edition and some new draft chapters from planned 3rd Edition.

• Between 10 and 15 research papers from recent conferences/journals in Computational Linguistics and related fields (see below).

• Natural Language Processing with Python: Bird, Steven; Klein, Ewan, Loper, Edward. n, O'Reilly, 2009. Free HTML version. You can order this book directly from O'Reilly

• Introduction to Information Retrieval. by Manning, Raghavan, Schutze webpage

• Graph-based Natural Language Processing and Information Retrieval. Rada Mihalcea (Author), Dragomir Radev (Author)

• Foundations of Statistical Natural Language Processing by Christopher D. Manning, Hinrich Schutze. (M&S). In many cases the statistical approaches are covered in more detail in this book. However, it does not contain all the topics that we will cover in this course. This book also has a webpage.680 pages 1 edition (1999), M.I.T. Press/Triliteral, ISBN: 0262133601.  This book will be useful in cases where you want a different presentation of the same material that is required reading from J&M

• Contemporary Linguistics: An introduction by W. O'Grady, J. Archibald, M. Aronoff, J. Rees-Miller. 684 pages 5th Edition (2004). ISBN: 0312419368. This book will be useful in cases where you want a more detailed description of linguistic theories. It also contains lots of clear examples of linguistic phenomena. This book also has a webpage.

• Synthesis Lectures in Natural Language Processing webpage

Syllabus, Assignments, Software& Data

1	Jan 7 Th	Intro and Course Overview We will communicate through Connect : to log in use your CWL	J&M Chp. 1	Intro - ACL - NLP demos/videos - Ambiguity NLP toolkits: NLTK (Python), Stanford CoreNLP (java)
2	Jan 12 Tu	English Morphology and Finite State Machines: FSA and FST	J&M Chp. 2&3	Applications of FSTs in NLP Lauri Karttunen, CIAA, 2000. Assignment1on Connect (due Jan 21) Recent book and software Xerox: FiniteState Technology Finite State Utilities  (Van Noord)
3	Jan 14 Th	Finish FST + Stemming + Spelling	J&M Chp. 3&4	The Porter Stemmer (includes perl implementation) ProbInfoTheory Handout min-edit-dist demo  A spelling correction program based on a noisy channel model Kerninghan et al. COLING ,1990. minimal Python implementation of spelling correction (by P. Norvig)
4	Jan 19 Tu	Minimum Edit Distance + Probabilistic Models: N-grams -  N-grams  Evaluation -	J&M Chp. 4	Google ngrams model Google books Ngrams viewer An empirical study of smoothing techniques for NLP S.F. Chen, J. Goodman - TR CS Harvard Univ - 1998 Stanford CoreNLP CMU-Cambridge language model toolkit SRI LM Toolkit
5	Jan 21 Th	Intro - Neural Networks and Neural Language Models - Start Markov Models	J&M Chp. 4-5-6	Neural Network Demos
6	Jan 26 Tu	Sequence Labelling Models - Part-of-speech Tagging	J&M Chp. 12	- state of the art POS tagging why tagging can be challenging for humans: Penn tagging scheme Part-of-Speech Tagging from 97% to 100% C. Manning 2011 Assignment2 on Connect (due Feb 11) Corpora: wsj-p.txt  wsj-ps.txt  atis3.pos.tags.txt cmpt-hw2-3.txt
7	Jan 28 Th	Start English Syntax and Context-free Grammars -- Parsing Algorithms	J&M Chp. 13	Interactive tutorials on the English grammar  English Dept. University of Calgary. - NLTK (demos) - look at *Getting Started*  - Some public parsers (inlcuding Stanford and MINIPAR visualization  tools)
8	Feb 2 Tu	Chunking / Dependency Grammars and Transition-based Dep. Parsing/ Treebanks -		Stanford Parser - -Popular Stat Parser - MaltParser - State of the Art Dependency Parser -Penn Treebank - Universal dependency Treebanks
9	Feb 4 Th	Probabilistic CFGs - PCFGs Parsing + Lexicalized PCFGs	J&M Chp. 14	- Berkeley Parser with demo!
10	Feb 9 Tu	Representing Meaning and Semantic Analysis	J&M Chp. 17-18	book on Computational Semantics Time ML Semantic Parser (Cornell - Yoav Artzi)
11	Feb 11 Th	Lexical Semantics	J&M Chp.19	- Wordnet and YAGO (Wikipedia + Wordnet + GeoNames). See also Probase and Freebase - (Domain specific thesaurus) Medical Subject Headings (MeSH) - FrameNet - ProbBank (adding semantic annotations to the Penn Treebank)
	Feb 15 - 19	mid-term Break
12	Feb 23 Tu	Computational Lexical Semantics (focus on Vector Semantics)	J&M Chp. 20 J&M Chp19, 3rd Ed. draft	- word2vec  - A systematic comparison of context-counting vs. context-predicting semantic vectors ! (predicting is clearly better) - generalization of skip-grams to sentences (skip-thought vectors) 2015 - SENSEVAL(Evaluation for WSD) - WSD online public systems - WSD with Deep Belief Networks - Dependency-based word similarity demo - TREC (Text REtrieval Conference) - Semantic Labeling (ASSERT) -Illinois Semantic Role Labeler Assignment3 onConnect (due March 15th)  needed files
13	Feb 25 Th	Pragmatics: Discourse&Dialog	J&M Chp.  21 & 24	- DAMSL - RST annotation tool
14	Mar 1 Tu	Project Proposal Presentations - see project work plan
		Natural Language Generation (NLG): sample system: Generator Evaluative Arguments (GEA)	handout	- SIGGEN - NLG systems book,    STOP system, SimpleNLG - NLG companies:   data2text  CoGenTex
		READINGS (what to do?)		avg. year 2010.5
15	Mar 3  Th	Generic Topic Modeling (background reading Comm. ACM) and Topic Modeling in Synchronous Conversations Steyvers, M. & Griffiths, T. (). Probabilistic topic models. In T. Landauer, D McNamara, S. Dennis, and W. Kintsch (eds), Latent Semantic Analysis: A Road to Meaning. Laurence Erlbaum 2006 [ pdf ] or [ pdf ]   [ Mansfield]   Galley, M., McKeown, K., Fosler-Lussier, E., & Jing, H. Discourse segmentation of multi-party conversation. In Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1, ACL ’03, Sapporo, Japan. ACL. 2003 [pdf]  [Hossain Imtiaz ]
16	Mar 8 Tu	Topic Modeling and Labelling in Asynchronous Conversations : S. Joty, G. Carenini and R. T. Ng (2013) Topic Segmentation and Labeling in Asynchronous Conversations JAIR, Volume 47, pages 521-573 (2013) [pdf]   NOTE: Split in two presentations. One student will cover topic segmentation [Masrani]  , the other topic labelling [Chen Jiahong]
17	Mar 10 Th	Visual Text Analytics and Interactive Topic Modeling E. Hoque and G. Carenini, ConVis: A Visual Text Analytic System for Exploring Blog Conversations, Journal of Computer Graphics Forum (Proc. EuroVis), 2014 [pdf]  [ Paul Bucci  ]   Jason Chuang, Sonal Gupta, Christopher D. Manning, Jeffrey Heer, Topic Model Diagnostics: Assessing Domain Relevance via Topical Alignment  [pdf]  [Mahdi Ghodsi ]
	Mar 15 Tu	class cancelled
18	Mar 17 Th	Natural Language Generation (Sentence Planning) Walker, M., Stent, A., Mairesse, F., & Prasad, R. (2007). Individual and domain adaptation in sentence planning for dialogue. Journal of Artificial Intelligence Research, 30, 413-456 2007. (long but lots of tables / figure)  pdf   [  Jacob Chen  ] Natural Language Generation (data2text) F Portet, E Reiter, A Gatt, J Hunter, S Sripada, Y Freer, C Sykes  Automatic Generation of Textual Summaries from Neonatal Intensive Care Data. Artificial Intelligence 173:789-816. 2009 (pdf)    [  Felipe Bañados Schwerter  ]
19	Mar 22 Tu	Summarization (1) Regina Barzilay, Kathleen McKeown "Sentence Fusion for Multidocument News Summarization", Computational Linguistics, 2005. [ps] [  Laura Tammpere ]   (background reading: textbook sec. 23.7 Summarization Evaluation) Lidong Bing, Piji Li, Yi Liao, Wai Lam, Weiwei Guo, Rebecca J. Passonneau,  Abstractive Multi-Document Summarization via Phrase Selection and Merging. Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics  (ACL 2015) pdf  [ Wenqiang Dong  ]
20	Mar 24 Th	Summarization (2) (Biographies) Fadi Biadsy, Julia Hirschberg, Elena Filatova, "An Unsupervised Approach to Biography Production using Wikipedia", ACL-08: HLT, Columbus, Ohio, Jun 2008 pdf [  Dmitry Tebaykin  ]    Janara Christensen, Stephen Soderland, Gagan Bansal, and Mausam "Hierarchical Summarization: Scaling Up Multi-Document Summarization" Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (ACL 2014) [pdf ]  [ Hindalong Emily   ]
21	Mar 29 Tu	Subjectivity and Sentiment Fangzhong Su and Katja Markert Subjectivity recognition on word senses via semi-supervised mincuts HLT- NAACL 2009 [  Yaashaar Hadadian   ] Theresa Wilson, Janyce Wiebe, and Paul Hoffmann (2009). Recognizing Contextual Polarity: An exploration of features for phrase-level sentiment analysis. Computational Linguistics, 35:3, pages 399-433.  [   Moumita Roy Tora ]
22	Mar 31 Th	Sentiment + Graph Based WSD Richard Socher, Alex Perelygin, Jean Wu, Jason Chuang, Christopher Manning, Andrew Ng and Christopher Potts, Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank Conference on Empirical Methods in Natural Language Processing (EMNLP 2013) [pdf] [ Nejat] Navigli, R. and Lapata, M. (2010) An experimental study of graph connectivity for unsupervised word sense disambiguation.  IEEE Transactions on Pattern Analysis and Machine Intelligence, 32(4), 678–692. [  Mehrdad Ghomi  ]
23	Apr 5 Tu	Discourse Parsing R. Soricut and D. Marcu. 2003. Sentence Level Discourse Parsing Using Syntactic and Lexical Information. NAACL 2003 [ pdf ]  [Jang]   portions of CL paper CODRA: A Novel Discriminative Framework  for Rhetorical Analysis.   Computational Linguistics (2015) Vol. 41, No. 3: 385–435, MIT press only sections 1 - 4 are mandatory  DEMO [ Johnson]
24	Apr 7 Th	More Discourse Parsing + Application Yang Liu and Sujian Li. Implicit discourse relation classification via multi-task neural networks. In Proceedings of AAAI Conference, (2016). [pdf] [Chen Jianhui]  Kelsey Allen, Giuseppe Carenini and Raymond Ng, Detecting Disagreement in Conversations using Pseudo-Monologic Rhetorical Structure - EMNLP-14 [ pdf ] [   Michael Haaf    ]
25	Apr 12 Tu	Project Update Presentations
26	?Apr 25?	Project Final Presentations Final Project Report Hand in