W03-1714 |
word-alignment semantic map obtained by
|
principle component analysis
|
( PCA ) . By comparing it with
|
W01-0514 |
primary distinction is , LSA applies
|
principle components analysis
|
to a word similarity matrix to
|
D14-1193 |
Capturing Hidden Component via
|
Principle Component Analysis
|
The first step of the proposed
|
H91-1011 |
dimensions resulting from our current
|
principle components analysis
|
is the best input for this type
|
H91-1011 |
linear discriminant functions and
|
principle components analysis
|
to allow for better modelling
|
S01-1008 |
space was reconstructed using
|
Principle Component Analysis
|
( PCA ) and Independent Component
|
W09-0701 |
In ( Nagroski et al. , 2003 ) ,
|
Principle Component Analysis
|
( PCA ) is used to cluster data
|
P09-2062 |
as multi-dimensional scaling ,
|
principle component analysis
|
and latent semantic analysis
|
P13-2038 |
al. , 2010 ) employed oriented
|
principle component analysis
|
and canonical correlation analysis
|
W14-3508 |
Sharoff et al. ( 2008 ) use a
|
Principle Component Analysis
|
to analyze the lexical and grammatical
|
W10-2801 |
transformed by first performing
|
Principle Component Analysis
|
and discarding the smallest principle
|
W09-4302 |
Moreover , the SVD and other forms of
|
principle component analysis
|
must have the entire corpus present
|
W03-0807 |
Latent Semantic Indexing , or
|
Principle Component Analysis
|
( PCA ) are also instances of
|
W10-0605 |
signal intact ( in this case a
|
principle components analysis
|
) proved very effective in preventing
|
W02-1609 |
confirmatory factor analysis and
|
principle components analysis
|
to identify the core set of evaluation
|
W12-3022 |
probabilistic generalization of
|
Principle Component Analysis
|
( gPCA ) to estimate the probabilities
|
D14-1138 |
der Maaten and Hinton , 2008 ) .
|
Principle Component Analysis
|
( PCA ) is a commonly-used dimensionality
|
N03-2033 |
criteria of the docu - ments .
|
Principle component analysis
|
( PCA ) revealed the same two
|
D12-1111 |
Because LSA is closely related to
|
principle component analysis
|
( PCA ) , extensions of PCA such
|
Q14-1020 |
to 500 dimensions by applying
|
principle component analysis
|
, a technique generally used
|