Processamento estatístico de linguagem natural - 2009



Local: sala C1-38
prof. Jorge Kinoshita


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


Programação PRELIMINAR aula a aula


10/6 
1. 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

17/6 
2. 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

24/6
4. 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.

01/7 
5. 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/
	

08/7 
6. word sense disambiguation
        ch. 7  
     http://www2.mta.ac.il/%7Egideon/courses/nlp/slides/word_sense_disambiguation.ppt

15/7
7. cadeias de Markov
        ch 9
	http://www2.mta.ac.il/%7Egideon/courses/nlp/slides/hmm.ppt




22/7
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
      


29/7
9. probabilistic context free languages 
     ch 11
     http://www2.mta.ac.il/%7Egideon/courses/nlp/slides/pcfg.ppt

05/8
	probabilistic parsing
	ch 12

12/8
10. clustering
    ch 14


19/8
11. information retrieval
     ch 15
     http://www2.mta.ac.il/%7Egideon/courses/nlp/slides/information_retrieval.ppt

26/8

12. text categorization
     ch 16
     http://www2.mta.ac.il/%7Egideon/courses/nlp/slides/text_categorization.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.


ficou de fora:

3. 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