ACM Home Page
Please provide us with feedback. Feedback
Latent semantic indexing: a probabilistic analysis
Full text PdfPdf (1.08 MB)
Source Symposium on Principles of Database Systems archive
Proceedings of the seventeenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems table of contents
Seattle, Washington, United States
Pages: 159 - 168  
Year of Publication: 1998
ISBN:0-89791-996-3
Authors
Christos H. Papadimitriou  Computer Science Division, U. C. Berkeley
Hisao Tamaki  Computer Science Department, Meiji University
Prabhakar Raghavan  IBM Almaden Research Center
Santosh Vempala  Department of Mathematics, M.I.T.
Sponsors
SIGART: ACM Special Interest Group on Artificial Intelligence
SIGMOD: ACM Special Interest Group on Management of Data
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 21,   Downloads (12 Months): 163,   Citation Count: 71
Additional Information:

references   cited by   index terms   collaborative colleagues  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/275487.275505
What is a DOI?

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
 
2
 
3
E. Brewer. Invited talk, 1997 PODS}SIGMOD, 1997.
 
4
S. Chakrabarti, B. Dora, D. Gibson, J. Kleinberg, P. Raghavan and S. Rajagopalan. "Mining information networks through spectral methods". In preparation, IBM Almaden Research Center, 1997.
 
5
D.M. Cvetkovi~, M. Doob, and H. Sachs, Spectra of Graphs, Academic Press, 1979.
 
6
S. Deerwester, S. T. Dumais, T.K. Landauer, G.W. Furnas, and R.A. Harshman. Indexing by latent semantic analysis. :Journal of the Society for Information Science, 41(6), 391-407, 1990.
7
 
8
S.T. Dumais. Improving the retrieval of information from external sources. Behavior Research Methods, Instruments and Computers, 23(2), 229- 236, 1991.
9
 
10
 
11
 
12
A. Frieze, R. Kannan and S. Vempala, "Fast Monte-Carlo Algorithms for finding low-rank approximations," preprint, http://wwwmath.mit.edu/vempala/papers/fastev.ps , 1998.
 
13
 
14
D. Gibson, J.M. Kleinberg and P. Rag.havan. "Using nonlinear dynamical systems to mine categorical data". Submitted for publication, 1997.
 
15
G. Golub and G. Reinsch. Handbook for matrix computation II, Linear Algebra. Springer-Veflag, New York, 1971.
 
16
G, H. Golub and G. F. Van Loan. Matrix computations. Johns Hopkins University Press, London, 1989.
 
17
W, Hoeffding. Probability inequalities for sums of bounded random variables, Journal of the American Statistical Association 58 13-30, 1963.
 
18
 
19
W, B. Johnson and J. Lindenstrauss. Extensions of Lipshitz mapping into Hflbert space, Contemp. Math. 26 (1984), 189-206.
 
20
 
21
 
22
 
23
 
24
 
25

CITED BY  72

Collaborative Colleagues:
Christos H. Papadimitriou: colleagues
Hisao Tamaki: colleagues
Prabhakar Raghavan: colleagues
Santosh Vempala: colleagues