Dalhousie University    [  http://web.cs.dal.ca/~vlado/csci6509/coursecalendar.html  ]
Winter 2015 (Jan5-Apr10)
Faculty of Computer Science
Dalhousie University

CSCI 4152/6509 - Course Calendar (tentative)

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  Part I: Introduction
1 Mon Jan  5Course Introduction
Course information: logistics and administrivia, textbook and other main references, evaluation scheme, academic integrity policy, tentative course schedule. Introduction to NLP (reading Ch.1 [JM]): natural language and other languages; NLP applications, NLP as a research area, NLP Research links and NLP Anthology http://aclweb.org/anthology-new/. Handout: Course syllabus
Files: Slides (PDF), Lecture notes (PDF). Reading: [JM] Ch.1
 
2 Wed Jan  7Introduction to Natural Language Processing
Short history of NLP. Levels of NLP.
Files: Slides (PDF), Lecture notes (PDF).
A0 out
3 Fri Jan  9About Course Project
Some reasons why NLP is hard, ambiguities at different levels of NLP, examples of lexical and syntactic ambiguities. Ambiguities at differenct levels of NLP (continued): syntactic, semantic, pragmatic levels; NLP metholodology; about course project: deliverables, P0, P1, P, R.
Files: Slides (PDF), Lecture notes (PDF).
 
  Part II: Stream-based Text Processing
4 Mon Jan 12 Introduction to Perl
About course project (continued): project types, choosing topic, resources; themes and previous topics. Part II: Stream-based Text Processing; Introduction to Perl, main Perl language features, strengths and weaknesses, resources, file names, running program, simple arithmetic, syntactic elements.
Files: Slides (PDF), Lecture notes (PDF).
 
5 Wed Jan 14Regular Expressions
Introduction to Perl (continued): reading input, declaring variables, counting lines. Regular expressions: reading: Section 2.1 [JM], simple example, use in Perl, examples.
Files: Slides (PDF), Lecture notes (PDF). Reading: Section 2.1 [JM]
A0 due
L1 Wed Jan 14Lab 1: SVN Tutorial Files: Slides (PDF), Lab notes (PDF). 
6 Fri Jan 16Elements of Morphology
Perl Examples: counting and extracting letters, words and sentences; Elements of Morphology: reading: Section 3.1 [JM]; morphemes, stems, affixes, tokenization, stemming, lemmatization; morphological processes.
Files: Slides(PDF), Lecture notes (PDF). Reading: Section 3.1 [JM]
 
7 Mon Jan 19Characters, Words, and N-grams
Morphological processes (continued): inflection, derivation, compounding; Characters, Words, and N-grams: Zipf's law, counting n-grams.
Files: Slides (PDF), Lecture notes (PDF).
 
8 Wed Jan 21N-grams
Counting n-grams, scalar vs. array context in Perl, subroutines in Perl; Using Ngrams module.
Files: Slides (PDF), Lecture notes (PDF).
 
L2 Wed Jan 21 Lab 2: Perl Tutorial 1 Files: Slides (PDF), Lab notes (PDF).A1 due
  Part III: Similarity-based Text Processing
9 Fri Jan 23Elements of Information Retrieval
Elements of information retrieval, basic task definition of ad-hoc retrieval, typical IR system architecture, vector space model, IR evaluation measures; example with precision-recall curves, other evaluation measures.
Files: Slides (PDF), Lecture notes (PDF). Reading: [JM] 23.1 (Information Retrieval), [MS] Ch.15 (Topics in Information Retrieval).
 
10 Mon Jan 26Similarity-based Text Classification
Text classification: introduction, CNG method, evaluating text classification, evaluation methods for classification.
Files: Slides (PDF), Lecture notes (PDF).
 
  Part IV: Probabilistic Approach to NLP
11 Wed Jan 28Probabilistic Approach to NLP
Evaluation methods for classification (continued); text clustering task description; Probabilistic approach to NLP: logical vs. plausible reasoning, plausibe reasoning approaches, probability theory as a plausible reasoning approach, brief probability theory elements review; Bayesian inference: generative models.
Files: Slides (PDF), Lecture notes (PDF).
 
L3 Wed Jan 28Lab 3: Perl Tutorial 2 Files: Slides (PDF), Lab notes (PDF).A2 due
12 Fri Jan 30Probabilistic Modeling
Bayesian inference (continued); Probabilistic modeling: random variables, random models, full and partial model configurations, computational tasks in probabilistic modeling, joint distribution model, spam example.
Files: Slides (PDF), Lecture notes (PDF).
 
13 Mon Feb 2Naive Bayes Model
Drawback of joint distribution model. Fully independent model. Naive Bayes classification model: assumption, graphical representation, parameters, example, computational tasks.
Files: Slides (PDF), Lecture notes (PDF).
P0 due
14 Wed Feb 3N-grams Model
Naive Bayes model (continued). N-gram model: assumption, graphical representation, n-gram model as Markov chain, perplexity.
Files: Slides (PDF), Lecture notes (PDF). Reading: [JM] Ch 4
 
L4 Wed Feb 4Lab 4: Perl Tutorial 3 Files: Slides (PDF), Lab notes (PDF), Additional slides (PDF).A3 due
  Fri Feb 6Munro Day, University closed, no class  
15 Mon Feb 9Smoothing
Use of language modeling in classification. Smoothing: add-one, Witten-Bell discounting, example.
Files: Slides (PDF), Lecture notes (PDF).
 
16 Wed Feb 11P0 Projects discussion
Discussion about projects (not finished).
Files: Slides (PDF), Lecture notes (PDF).
 
  Thu Feb 12Assignment 4 due A4 due
17 Fri Feb 13POS Tags
Discussion about projects (finished). Parts-of-speech (POS), reading: [JM] Sec 5.1-5.3.
Files: Slides (PDF), Lecture notes (PDF). Reading: [JM] Sec 5.1-5.3. (POS)
 
  Mon Feb 16Study break Mon-Sun, Feb 16-20  
18 Mon Feb 23Hidden Markov Model
POS (continued): adverbs, other classes, examples. Hidden Markov Model: definition, HMM assumption, applications, POS tagging using HMM, computational tasks.
Files: Slides (PDF), Lecture notes (PDF). Reading: [JM] Ch. 6 (HMM, first part)
 
19 Wed Feb 25Bayesian Networks
HMM POS Example: brute-force approach, dynamic programming approach, Viterbi algorithm; Bayesian Networks: definition, assumption, example, why is inference in BNs expensive.
Files: Slides (PDF), Lecture notes (PDF). Reading: Sec 5.5 (HMM POS tagging)
A5 due
20 Fri Feb 27Product-Sum Algorithms Files: Slides (PDF), Lecture notes (PDF). 
  Part V: Parsing (Syntactic Processing)
21 Mon Mar 2Context-free Grammars and NLP P1 due
22 Wed Mar 4CYK Parsing  
23 Fri Mar 6Probabilistic Contex-Free Grammar  
  Part IV: Semantics and Unification-based NLP
24 Mon Mar 9Introduction to Unification-based Approach to NLP  
25 Wed Mar 11Resolution and Unification  
L5 Wed Mar 11Lab 5: Prolog Tutorial 1  
26 Fri Mar 13Unification Algorithms  
27 Mon Mar 16DCG -- Definite Clause Grammars  
28 Wed Mar 18Feature Structures  
L6 Wed Mar 18Lab 6: Prolog Tutorial 2  
29 Fri Mar 20 Unification-based Grammars and Chart Parsing  
30 Mon Mar 23Course Review  
  Part VII: Student Presentations
31 Wed Mar 25Student presentations (PT-32, PT-33, PT-34, PT-35)  
32 Fri Mar 27 Student presentations (PT-28, PT-29, PT-30, PT-31)  
33 Mon Mar 30Student presentations (PT-24, PT-25, PT-26, PT-27)  
34 Wed Apr 1Student presentations (PT-20, PT-21, PT-22, PT-23)  
35 Wed Apr 1(LAB) Student presentations (PT-16, PT-17, PT-18, PT-19)  
  Fri Apr  3Good Friday, University closed, no class  
36 Mon Apr 6Student presentations (PT-12, PT-13, PT-14, PT-15)  
37 Wed Apr 8 Student presentations (PT-08, PT-09*, PT-10, PT-11)
PT-09: Nisha Simon.
 
38 Wed Apr 8 Student presentations (Lab) (PT-04, PT-05, PT-06, PT-07)  
39 Fri Apr 10 Student presentations, Course Evaluation (PT-01, PT-02, PT-03) Report due
  Thu Apr 16Final Exam (12:00-14:00)
Final exam, duration 2 hours, starting at 12:00, location not posted yet. Exam schedule URL: http://www.dal.ca/academics/exam_schedule/halifax_campus_exam_schedule.html
Exam

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