Analysis of unsupervised dimensionality reduction techniques

Computer Science and Information Systems

Volumn 6, Issue 2, 2009, Pages 217-227

  Kumar, Ch Aswani ^a  

^a VIT UNIVERSITY   (India)

Author keywords

Dimensionality reduction; Information retrieval; Latent semantic indexing; Matrix decompositions

Indexed keywords

EID: 77953845946     PISSN: 18200214     EISSN: None     Source Type: Journal    
DOI: 10.2298/CSIS0902217K     Document Type: Article

References (23)

1. Aswani Kumar, Ch., Srinivas, S.: Latent semantic indexing using eigenvalue analysis for efficient information retrieval. International Journal of Applied Mathematics and Computer Science, Vol. 16, No. 4, 551-558. (2006)
2. Aswani Kumar, Ch., Srinivas, S.: A note on the effect of term weighting on selecting intrinsic dimensionality of data, Cybernetics and Information Technologies, Vol. 9, No. 1, 5-12. (2009)
3. Aswani Kumar, Ch., Srinivas, S.: Automatic selection of intrinsic dimensionality of data, International Journal on Information Processing, Vol. 3, No. 2, 8-16. (2009)
4. Aswani Kumar, Ch., Srinivas, S.: On the performance of latent semantic indexing based information retrieval, Journal of Computing and Information Technology, Vol. 17, No. 3, 259-264. (2009)
5. Berry, M.W., Browne, M., Langville, A.N., Pauca, V.P., Plemmons, R.J.:Algorithms and applications for approximate nonnegative matrix factorization. Computational Statistics and Data Analysis. Vol. 52, No.1, 155-173. (2007)
6. Cunningham, P.:Dimension reduction. Technical Report: UCD-CSI-2007-7. (2007)
7. Deerwester, S., Dumais, S., Furnas, G., Landauer, T, Harshman, R.:Indexing by latent semantic analysis, Journal of the American Society for Information Science. Vol. 41, No. 6, 391-407. (1990)
8. Dhillon, I.S., Modha, D.S.: Concept decomposition for large sparse text data using clustering. Machine Learning, Vol. 42, No. 1, 143-175. (2001)
9. Dobsa, J., Dalbelo-Basic, B.: Concept decomposition by fuzzy k-means algorithm. In Proceedings International conference on Web Intelligence. 684-688. (2003)
10. Doring, C., Lesot, M.J., Kruse, R.: Data analysis with fuzzy clustering methods. Computational statistics and data analysis. Vol. 51, No. 1, 192-214. (2006)
11. Foder, I.K.: A survey of dimension reduction techniques. Technical report URL-ID-148494, Center for applied scientific computing, Lawrence Livermore National Laboratory. (2002)
12. Hyvarinen, A., Oja, E.: Independent component analysis: Algorithms and applications. Neural Networks. Vol. 13, No. 4-5, 411-430. (2000)
13. Kolenda, T., Hansen, L.K., Sigurdsson, S.: Independent components in text. Advances in Independent Component Analysis. Springer-Verlag. (2000)
14. Lee, D.D., Seung, H.S.: Algorithms for non-negative matrix factorization. Advances in Neural Information Processing Systems. Vol. 13, 556-562. (2001)
15. Lee, D.D., Seung, H.S.: Learning the parts of objects by non-negative matrix factorization. Nature. Vol. 401, 788-791. (1999)
16. Moravec, P.: Testing dimensional reduction methods for text retrieval. In Proceedings of Dateso 2005 Annual international workshop on databases. 113-124. (2005)
17. Shahnaz, F., Berry, M.W., Paul Pauca, V., Plemmons, R.J.: Document clustering using non-negative matrix factorization. Information Processing and Management. Vol. 42, No.2, 373-386. (2006)
18. Skillicorn, D.B., McConnell, S.M., Soong, E.Y.: Handbook of data mining using matrix decompositions. Queen's University, Canada. (2003)
19. Srinivas, S., Aswani Kumar, Ch.: Optimizing heuristics in latent semantic indexing for effective information retrieval. Journal of Information and Knowledge Management. Vol. 5, No. 2, 97-105. (2006)
20. Vinay, V., Cox, I.J., Wood, K., Milic-Frayling, N.: A comparison of dimensionality reduction techniques for text retrieval. In Proceedings of 4th International conference on machine learning and applications.293-298. (2005)
21. Yan, J., Zhang, B., Liu, N., Yan, S., Cheng, Q., Fan, W., Yang, Q., Xi, W., Chen, Z.: Effective and efficient dimensionality reduction for large-scale and streaming data preprocessing, IEEE Transaction on Knowledge and Data Engineering, Vol.18, No. 3, 320-333. (2006)
22. http://www.cis.hut.fi/projects/ica/fastica/
23. http://www.mathworks.com