PLSI utilization for automatic thesaurus construction

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3651 LNAI, Issue , 2005, Pages 334-345

  Hagiwara, Masato ^a   Ogawa, Yasuhiro ^a   Toyama, Katsuhiko ^a  

^a NAGOYA UNIVERSITY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL METHODS; DATABASE SYSTEMS; LSI CIRCUITS; MATHEMATICAL MODELS; NATURAL LANGUAGE PROCESSING SYSTEMS; PERFORMANCE;

LOW FREQUENCIES; SURFACE INFORMATION; THESAURUS CONSTRUCTION;

SEMANTICS;

EID: 33645968654     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11562214_30     Document Type: Conference Paper

References (17)

1. Bilmes, J. 1997. A gentle tutorial on the EM algorithm and its application to parameter estimation for gaussian mixture and hidden markov models. Technical Report ICSI-TR-97-021, International Computer Science Institute (ICSI), Berkeley, CA.
2. Charniak, E. 2000. A maximum-entropy-inspired parser. NAACL 1, 132-139.
3. Collins. 2002. Collins Cobuild Major New Edition CD-ROM. HarperCollins Publishers.
4. Collins, M. 1996. A new statistical parser based on bigram lexical dependencies. Proc. of 34th ACL, 184-191.
5. Deerwester, S., et al. 1990. Indexing by Latent Semantic Analysis. Journal of the American Society for Information Science, 41(6):391-407.
6. Fellbaum, C. 1998. WordNet: an electronic lexical database. MIT Press.
7. Hindle, D. 1990. Noun classification from predicate-argument structures. Proc. of the 28th Annual Meeting of the ACL, 268-275.
8. Hofmann, T. 1999. Probabilistic Latent Semantic Indexing. Proc. of the 22nd International Conference on Research and Development in Information Retrieval (SIGIR '99), 50-57.
9. Hofmann, T. 2001. Unsupervised Learning by Probabilistic Latent Semantic Analysis. Machine Learning, 42:177-196.
10. Kojima, K., et. al. 2004. Existence and Application of Common Threshold of the Degree of Association. Proc. of the Forum on Information Technology (FIT2004) F-003.
11. Lee, L. 2001. On the Effectiveness of the Skew Divergence for Statistical Language Analysis. Artificial Intelligence and Statistics 2001, 65-72.
12. Lin, J. 1991. Divergence measures based on the shannon entropy. IEEE Transactions on Information Theory, 37(1):140-151.
13. Mochihashi, D., Matsumoto, Y. 2002. Probabilistic Representation of Meanings. IPSJ SIG-Notes Natural Language, 2002-NL-147:77-84.
14. The National Institute of Japanese Language. 2004. Bunruigoihyo. Dainippontosho.
15. Santorini, B. 1990. Part-of-Speech Tagging Guidelines for the Penn Treebank Project. ftp://ftp.cis.upenn.edu/pub/treebank/doc/tagguide.ps.gz
16. Schmid, H. 1994. Probabilistic Part-of-Speech Tagging Using Decision Trees. Proc. of the First International Conference on New Methods in Natural Language Processing (NemLap-94), 44-49.
17. Ueda, N., Nakano, R. 1998. Deterministic annealing EM algorithm. Neural Networks, 11:271-282.