Processamento estatístico de linguagem natural - 2006

junho a setembro de 2006

Local: sala B2-04
prof. Jorge Kinoshita


livro texto: 
Foundations of Statistical Natural Language Processing
Manning C.D; Shutze,H.
MIT Press.


Programação PRELIMINAR aula a aula


1  28/6 
Apresentação do curso, "natural language and statistics",  
	ch. 1 - Introduction
	http://www2.mta.ac.il/%7Egideon/courses/nlp/slides/introduction.ppt
	texto para discussao em sala:
	Chomsky influenciou contra o processamento estatistico de linguagem natural: 
		http://en.wikipedia.org/wiki/Poverty_of_stimulus

2  06/7 
fundamentos matemáticos
	ch. 2
	http://www2.mta.ac.il/%7Egideon/courses/nlp/slides/mathematical_foundations.ppt
	http://l2r.cs.uiuc.edu/%7Edanr/Teaching/CS598-04/Lectures/Lec4-Math.pdf

3  13/7
 fundamentos linguísticos; corpus 
	ch. 3,4
	http://www2.mta.ac.il/%7Egideon/courses/nlp/slides/linguistic_essentials.ppt
	http://l2r.cs.uiuc.edu/~danr/Teaching/CS497-00/Lectures/2linguistics.ps 
	http://l2r.cs.uiuc.edu/~danr/Papers/spellJ.ps.gz

4  20/7 
colocações
	ch. 5
	http://www2.mta.ac.il/%7Egideon/courses/nlp/slides/collocations.ppt
	http://nlp.stanford.edu/fsnlp/promo/colloc.pdf 
	- http://www.d.umn.edu/~tpederse/nsp.html 

	Algoritmos:
	desvios na media e varianca.
	t-student
	chi square 
	informacao mutua.
	

5  27/7 
n-grams
	ch. 6
	http://www2.mta.ac.il/%7Egideon/courses/nlp/slides/ngrams.ppt
	http://l2r.cs.uiuc.edu/%7Edanr/Teaching/CS598-04/Lectures/Lec5-Stat.pdf 
	http://research.microsoft.com/~joshuago/longcombine.pdf
	http://l2r.cs.uiuc.edu/%7Edanr/Teaching/CS598-04/Papers/Chen-Goodman-smoothing.pdf 
	- http://www.speech.sri.com/projects/srilm/

6  03/8
word sense disambiguation
        ch. 7  
     http://www2.mta.ac.il/%7Egideon/courses/nlp/slides/word_sense_disambiguation.ppt



7  10/8
cadeias de Markov
        ch 9
	http://www2.mta.ac.il/%7Egideon/courses/nlp/slides/hmm.ppt



8  17/8
part of speech tagging (foco no uso das redes de Markov).
     ch 10 
     http://www2.mta.ac.il/%7Egideon/courses/nlp/slides/pos.ppt
      
probabilistic context free languages 
     ch 11
     http://www2.mta.ac.il/%7Egideon/courses/nlp/slides/pcfg.ppt



9  24/8
text categorization
     ch 16
     http://www2.mta.ac.il/%7Egideon/courses/nlp/slides/text_categorization.ppt

10 31/8
information retrieval
     ch 15
     http://www2.mta.ac.il/%7Egideon/courses/nlp/slides/information_retrieval.ppt




Trabalho do curso:
- escolher algoritmos das aulas 4-9 e implementar. Explicar algoritmo em classe, trazendo um exercicio sobre ele.

Nota: 0.7 * T + 0.3 * E

onde 
T = trabalho 
E = media dos exercicios em classe.