Name
Abstract | ||
|---|---|---|
The technique described in this paper is similar to latent semantic indexing (LSI),although with some variation. Whereas LSI operates by performing a singular valuedecomposition (SVD) on a large term by document matrix of co-occurrence scores, thetechnique here operates by identifying eigenvectors and eigenvalues of a term by termmatrix of correlation scores (derived from co-occurrence scores). The technique ofidentifying eigenvectors and eigenvalues from a correlation matrix is known as... |
Year | Venue | Keywords |
|---|---|---|
1997 | Text REtrieval Conference | singular value decomposition,eigenvalues,principal component analysis,latent semantic indexing,eigenvectors,correlation matrix |
Field | DocType | Citations |
Data mining,Singular value decomposition,Eigenface,Pattern recognition,Computer science,Modal matrix,Document-term matrix,Artificial intelligence,Singular spectrum analysis,Latent semantic analysis,Matrix differential equation,Principal component analysis | Conference | 4 |
PageRank | References | Authors |
0.96 | 1 | 1 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gregory B. Newby | 1 | 220 | 32.13 |