Generalized hebbian algorithm for incremental singular value decomposition in natural language processing

EACL 2006 - 11th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference

Volumn , Issue , 2006, Pages 97-104

  Gorrell, Genevieve ^a  

^a LINKÖPING UNIVERSITY   (Sweden)

Author keywords

[No Author keywords available]

Indexed keywords

GENERALIZED HEBBIAN ALGORITHM; INCREMENTAL SINGULAR VALUE DECOMPOSITIONS; LARGE DATASETS; MEMORY REQUIREMENTS; NATURAL LANGUAGE PROCESSING; NATURAL LANGUAGES;

COMPUTATIONAL LINGUISTICS; NATURAL LANGUAGE PROCESSING SYSTEMS; SINGULAR VALUE DECOMPOSITION;

ALGORITHMS;

EID: 42149186171     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (12)

1. J. Bellegarda. 2000. Exploiting latent semantic information in statistical language modeling. Proceedings of the IEEE, 88: 8.
2. Michael W. Berry, Susan T. Dumais, and Gavin W. O'Brien. 1995. Using linear algebra for intelligent information retrieval. SIAM Review, 34(4): 573-595.
3. R. W. Berry. 1992. Large-scale sparse singular value computations. The International Journal of Supercomputer Applications, 6(1): 13-49.
4. Scott C. Deerwester, Susan T. Dumais, Thomas K. Landauer, George W. Furnas, and Richard A. Harshman. 1990. Indexing by latent semantic analysis. Journal of the American Society of Information Science, 41(6): 391-407.
5. S. Dumais. 1990. Enhancing performance in latent semantic indexing. TM-ARH-017527 Technical Report, Bellcore, 1990.
6. G. H. Golub and C. Reinsch. 1970. Handbook series linear algebra. singular value decomposition and least squares solutions. Numerical Mathematics, 14: 403-420.
7. G. Gorrell and B. Webb. 2005. Generalized hebbian algorithm for latent semantic analysis. In Proceedings of Interspeech 2005.
8. P. Kanerva, J. Kristoferson, and A. Holst. 2000. Random indexing of text samples for latent semantic analysis. In Proceedings of 22nd Annual Conference of the Cognitive Science Society.
9. E. Oja and J. Karhunen. 1985. On stochastic approximation of the eigenvectors and eigenvalues of the expectation of a random matrix. J. Math. Analysis and Application, 106: 69-84.
10. Terence D. Sanger. 1989. Optimal unsupervised learning in a single-layer linear feedforward neural network. Neural Networks, 2: 459-473.
11. Terence D. Sanger. 1993. Two iterative algorithms for computing the singular value decomposition from input/output samples. NIPS, 6: 144-151.
12. Juyang Weng, Yilu Zhang, and Wey-Shiuan Hwang. 2003. Candid covariance-free incremental principal component analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence, 25: 8: 1034-1040.