Topic-based language models using dirichlet mixtures

Systems and Computers in Japan

Volumn 38, Issue 12, 2007, Pages 76-85

  Sadamitsu, Kugatsu ^a   Mishina, Takuya ^b   Yamamoto, Mikio ^a  

^a UNIVERSITY OF TSUKUBA   (Japan)

^b IBM RESEARCH   (United States)

Author keywords

Aspect model; EM algorithm; LDA; Probabilistic LSA; Statistical language model

Indexed keywords

MATHEMATICAL MODELS; PARAMETER ESTIMATION; PROBABILITY; PROGRAM DOCUMENTATION; STATISTICAL METHODS; TEXT PROCESSING;

ASPECT MODELS; EM ALGORITHM; PROBABILISTIC LSA; STATISTICAL LANGUAGE MODEL;

COMPUTER PROGRAMMING LANGUAGES;

EID: 34648828370     PISSN: 08821666     EISSN: 1520684X     Source Type: Journal    
DOI: 10.1002/scj.20629     Document Type: Article

References (13)

1. Deerwester SC, Dumais ST, Landauer TK, Furnas GW, Harshman RA. Indexing by latent semantic analysis. J Am Soc Inf Sci 1990;41:391-407.
2. Hofmann T. Probabilistic latent semantic indexing. Proc 22nd Annual ACM Conference on Research and Development in Information Retrieval, p 50-57, Berkeley, California, 1999.
3. Gildea D, Hofmann T. Topic-based language models using em. Proc 6th European Conference on Speech Communication and Technology (EURGSPEECH), p 2167-2170, 1999.
4. Mishina T, Yamamoto M. Context adaptation using variational Bayesian learning of n-gram models based on probabilistic LSA. Tech Rep IEICE 2002;NLC-2002-73.
5. Takahashi R, Minematsu N, Hirose K. Language model using context adaptation for dynamic interpolation of multiple N-grams. Joho Gakkenho, NL-155, p 37-42, 2003.
6. Ueda N. Bayesian learning II, IV. J IEICE 2002:85:421-426, 633-638.
7. Blei DM, Ng AY, Jordan MI, Latent Dirichlet allocation. Neural Information Processing Systems, Vol. 14, 2002.
8. Sjölander K, Karplus K, Brown M, Hunghey R, Krogh A, Mian IS, Haussler D. Dirichlet mixtures: A method for improved detection of weak but significant protein sequence homology. Comput Appl Biosci 1996;12:327-345.
9. Church KW, Gale W. Poisson mixtures. Nat Language Eng 1995;1:163-190.
10. Iyer RM, Gstendorf M. Modeling long distance dependence in language: Topic mixtures versus dynamic cache models. IEEE Trans Speech Audio Process 1999;7:30-39.
11. Nigam STK, McCallum A, Mitchell T. Text classification from labeled and unlabeled documents using EM. Mach Learn 2000;39:103-134.
12. Minka T. Estimating a Dirichlet distribution, http: //www.stat.cmu.edu/ ~minka/papers/dirichlet/, 2003.
13. Ueda N. New developments in text modeling. Gengo Shori Gakkai Ninth Annual Conference, Tutorial Materials, p 1-17, 2003.