other,6-1-P06-2110,bq |
This paper examines what kind of
<term>
similarity
</term>
between
<term>
words
</term>
can be represented by what kind of
<term>
word vectors
</term>
in the
<term>
vector space model
</term>
.
|
#11476
This paper examines what kind ofsimilarity between words can be represented by what kind of word vectors in the vector space model. |
other,8-1-P06-2110,bq |
This paper examines what kind of
<term>
similarity
</term>
between
<term>
words
</term>
can be represented by what kind of
<term>
word vectors
</term>
in the
<term>
vector space model
</term>
.
|
#11478
This paper examines what kind of similarity betweenwords can be represented by what kind of word vectors in the vector space model. |
other,16-1-P06-2110,bq |
This paper examines what kind of
<term>
similarity
</term>
between
<term>
words
</term>
can be represented by what kind of
<term>
word vectors
</term>
in the
<term>
vector space model
</term>
.
|
#11486
This paper examines what kind of similarity between words can be represented by what kind ofword vectors in the vector space model. |
other,20-1-P06-2110,bq |
This paper examines what kind of
<term>
similarity
</term>
between
<term>
words
</term>
can be represented by what kind of
<term>
word vectors
</term>
in the
<term>
vector space model
</term>
.
|
#11490
This paper examines what kind of similarity between words can be represented by what kind of word vectors in thevector space model. |
tech,5-2-P06-2110,bq |
Through two experiments , three
<term>
methods for constructing word vectors
</term>
, i.e. ,
<term>
LSA-based , cooccurrence-based and dictionary-based methods
</term>
, were compared in terms of the ability to represent two kinds of
<term>
similarity
</term>
, i.e. ,
<term>
taxonomic similarity
</term>
and
<term>
associative similarity
</term>
.
|
#11499
Through two experiments, threemethods for constructing word vectors, i.e., LSA-based, cooccurrence-based and dictionary-based methods, were compared in terms of the ability to represent two kinds of similarity, i.e., taxonomic similarity and associative similarity. |
other,13-2-P06-2110,bq |
Through two experiments , three
<term>
methods for constructing word vectors
</term>
, i.e. ,
<term>
LSA-based , cooccurrence-based and dictionary-based methods
</term>
, were compared in terms of the ability to represent two kinds of
<term>
similarity
</term>
, i.e. ,
<term>
taxonomic similarity
</term>
and
<term>
associative similarity
</term>
.
|
#11507
Through two experiments, three methods for constructing word vectors, i.e.,LSA-based , cooccurrence-based and dictionary-based methods, were compared in terms of the ability to represent two kinds of similarity, i.e., taxonomic similarity and associative similarity. |
other,32-2-P06-2110,bq |
Through two experiments , three
<term>
methods for constructing word vectors
</term>
, i.e. ,
<term>
LSA-based , cooccurrence-based and dictionary-based methods
</term>
, were compared in terms of the ability to represent two kinds of
<term>
similarity
</term>
, i.e. ,
<term>
taxonomic similarity
</term>
and
<term>
associative similarity
</term>
.
|
#11526
Through two experiments, three methods for constructing word vectors, i.e., LSA-based, cooccurrence-based and dictionary-based methods, were compared in terms of the ability to represent two kinds ofsimilarity, i.e., taxonomic similarity and associative similarity. |
other,36-2-P06-2110,bq |
Through two experiments , three
<term>
methods for constructing word vectors
</term>
, i.e. ,
<term>
LSA-based , cooccurrence-based and dictionary-based methods
</term>
, were compared in terms of the ability to represent two kinds of
<term>
similarity
</term>
, i.e. ,
<term>
taxonomic similarity
</term>
and
<term>
associative similarity
</term>
.
|
#11530
Through two experiments, three methods for constructing word vectors, i.e., LSA-based, cooccurrence-based and dictionary-based methods, were compared in terms of the ability to represent two kinds of similarity, i.e.,taxonomic similarity and associative similarity. |
other,39-2-P06-2110,bq |
Through two experiments , three
<term>
methods for constructing word vectors
</term>
, i.e. ,
<term>
LSA-based , cooccurrence-based and dictionary-based methods
</term>
, were compared in terms of the ability to represent two kinds of
<term>
similarity
</term>
, i.e. ,
<term>
taxonomic similarity
</term>
and
<term>
associative similarity
</term>
.
|
#11533
Through two experiments, three methods for constructing word vectors, i.e., LSA-based, cooccurrence-based and dictionary-based methods, were compared in terms of the ability to represent two kinds of similarity, i.e., taxonomic similarity andassociative similarity. |
other,8-3-P06-2110,bq |
The result of the comparison was that the
<term>
dictionary-based word vectors
</term>
better reflect
<term>
taxonomic similarity
</term>
, while the
<term>
LSA-based and the cooccurrence-based word vectors
</term>
better reflect
<term>
associative similarity
</term>
.
|
#11544
The result of the comparison was that thedictionary-based word vectors better reflect taxonomic similarity, while the LSA-based and the cooccurrence-based word vectors better reflect associative similarity. |
other,13-3-P06-2110,bq |
The result of the comparison was that the
<term>
dictionary-based word vectors
</term>
better reflect
<term>
taxonomic similarity
</term>
, while the
<term>
LSA-based and the cooccurrence-based word vectors
</term>
better reflect
<term>
associative similarity
</term>
.
|
#11549
The result of the comparison was that the dictionary-based word vectors better reflecttaxonomic similarity, while the LSA-based and the cooccurrence-based word vectors better reflect associative similarity. |
other,18-3-P06-2110,bq |
The result of the comparison was that the
<term>
dictionary-based word vectors
</term>
better reflect
<term>
taxonomic similarity
</term>
, while the
<term>
LSA-based and the cooccurrence-based word vectors
</term>
better reflect
<term>
associative similarity
</term>
.
|
#11554
The result of the comparison was that the dictionary-based word vectors better reflect taxonomic similarity, while theLSA-based and the cooccurrence-based word vectors better reflect associative similarity. |
other,26-3-P06-2110,bq |
The result of the comparison was that the
<term>
dictionary-based word vectors
</term>
better reflect
<term>
taxonomic similarity
</term>
, while the
<term>
LSA-based and the cooccurrence-based word vectors
</term>
better reflect
<term>
associative similarity
</term>
.
|
#11562
The result of the comparison was that the dictionary-based word vectors better reflect taxonomic similarity, while the LSA-based and the cooccurrence-based word vectors better reflectassociative similarity. |