Elaborazione del Linguaggio Naturale

Laurea Magistrale: Informatica.

Docente: Giuseppe Attardi Ricevimento: Mercoledì, 11:00

Prerequisiti

Introduction
1. History
2. Present and Future
3. NLP and the Web
Mathematical Background
1. Probability and Statistics
2. Language Model
3. Hidden Markov Model
4. Viterbi Algorithm
5. Generative vs Discriminative Models
Linguistic Essentials
1. Part of Speech and Morphology
2. Phrase structure
3. Collocations
4. n-gram Models
5. Word Sense Disambiguation
Preprocessing
1. Encoding
2. Regular Expressions
3. Segmentation
4. Tokenization
5. Normalization
NLTK
1. Introduction to Python
2. Overvies of NLTK libraries
Classification
1. Machine Learning
2. Statistical classifiers
  1. Bayesan Network
  2. Perceptron
  3. Maximum Entropy
  4. Support Vector Machines
  5. Hidden Variable Models
Clustering
1. K-means
2. Factored Models
  1. Singular Value Decomposition
  2. Latent Semantic Indexing
Tagging
1. Part of Speech
2. Named Entity
3. Super Senses
Sentence Structure
1. Constituency Parsing
2. Dependency Parsing
Semantic Analysis
1. Semantic Role Labeling
2. Coreference resolution
Statistical Machine Translation
1. Word-Based Models
2. Phrase-Based Models
3. Decoding
4. Syntax-Based SMT
5. Evaluation metrics
Processing Pipelines
1. Integrated tooolkit
2. Frameworks
  1. Gate
  2. UIMA
3. Data Pipeline
  1. Tanl
Applications
1. Information Extraction
2. Information Filtering
3. Recommender System
4. Opinion Mining
5. Semantic Search
6. Question Answering
  1. Text Entailment

Date	Lecture	Notes
8/03/2011	Introduction
11/3/2011	Introduction to probability (slides)
15/03/2011	Python Tutorial (slides)	Homework 1, NPS chat collection
18/03/2011	Homework Solution
22/03/2011	Text Classification (slides)
25/03/2011	Naive Bayes Classifier
29/03/2011	Introduction to NLTK (slides)
1/04/2011	Segmentation and Tokenization (slides)
5/04/2011	Hidden Markov Model (slides)
8/04/2011	Named Entity Recognition (slides)
12/04/2011	Maximum Entropy Models (slides)
29/04/2011	Perceptron, SVM
03/05/2011	Dependency Parsing (Dependency Formalism , Dependency Parsing )
13/05/2011	MEMM	Homework 2
24/05/2011	Machine Translation (MT)
27/05/2011	Phrase Based Statistical Machine Translation (PBMT)
31/05/2011	Conditional Random Fields (D. Marcheggiani), Recommender Systems I. Sansovino}})
7/06/2011	Sentiment Analysis ( G. Righetti)

C. Manning, H. Schutze. Foundations of Statistical Natural Language Processing. MIT Press, 2000.
D. Jurafsky, J.H. Martin, Speech and Language Processing. 2nd edition, Prentice-Hall, 2008.
S. Kubler, R. McDonald, J. Nivre. Dependency Parsing. 2010.
P. Koehn. Statistical Machine Translation. Cambridge University Press, 2010.
S. Bird, E. Klein, E. Loper. Natural Language Processing with Python.

Progetto e orale.