other,16-2-P04-2005,bq |
<term>
topic signature
</term>
is a set of
<term>
|
words
|
</term>
that tend to co-occur with it .
<term>
|
#6921
Given a particular concept, or word sense, a topic signature is a set ofwords that tend to co-occur with it. |
other,15-4-P04-2005,bq |
word senses
</term>
are lexicalised in
<term>
|
English
|
</term>
and
<term>
Chinese
</term>
, and also
|
#6973
Our method takes advantage of the different way in which word senses are lexicalised inEnglish and Chinese, and also exploits the large amount of Chinese text available in corpora and on the Web. |
other,17-4-P04-2005,bq |
lexicalised in
<term>
English
</term>
and
<term>
|
Chinese
|
</term>
, and also exploits the large amount
|
#6975
Our method takes advantage of the different way in which word senses are lexicalised in English andChinese, and also exploits the large amount of Chinese text available in corpora and on the Web. |
other,3-5-P04-2005,bq |
<term>
Web
</term>
. We evaluated the
<term>
|
topic signatures
|
</term>
on a
<term>
WSD
</term>
task , where
|
#6997
We evaluated thetopic signatures on a WSD task, where we trained a second-order vector co-occurrence algorithm on standard WSD datasets, with promising results. |
lr,34-4-P04-2005,bq |
available in
<term>
corpora
</term>
and on the
<term>
|
Web
|
</term>
. We evaluated the
<term>
topic signatures
|
#6992
Our method takes advantage of the different way in which word senses are lexicalised in English and Chinese, and also exploits the large amount of Chinese text available in corpora and on theWeb. |
tech,7-5-P04-2005,bq |
the
<term>
topic signatures
</term>
on a
<term>
|
WSD
|
</term>
task , where we trained a
<term>
second-order
|
#7001
We evaluated the topic signatures on aWSD task, where we trained a second-order vector co-occurrence algorithm on standard WSD datasets, with promising results. |
tech,14-5-P04-2005,bq |
WSD
</term>
task , where we trained a
<term>
|
second-order vector co-occurrence algorithm
|
</term>
on standard
<term>
WSD datasets
</term>
|
#7008
We evaluated the topic signatures on a WSD task, where we trained asecond-order vector co-occurrence algorithm on standard WSD datasets, with promising results. |
other,3-2-P04-2005,bq |
signatures
</term>
. Given a particular
<term>
|
concept
|
</term>
, or
<term>
word sense
</term>
, a
<term>
|
#6908
Given a particularconcept, or word sense, a topic signature is a set of words that tend to co-occur with it. |
tech,9-3-P04-2005,bq |
</term>
can be useful in a number of
<term>
|
Natural Language Processing ( NLP )
|
</term>
applications , such as
<term>
Word
|
#6938
Topic signatures can be useful in a number ofNatural Language Processing ( NLP ) applications, such as Word Sense Disambiguation (WSD) and Text Summarisation. |
other,10-4-P04-2005,bq |
advantage of the different way in which
<term>
|
word senses
|
</term>
are lexicalised in
<term>
English
</term>
|
#6968
Our method takes advantage of the different way in whichword senses are lexicalised in English and Chinese, and also exploits the large amount of Chinese text available in corpora and on the Web. |
other,10-2-P04-2005,bq |
</term>
, or
<term>
word sense
</term>
, a
<term>
|
topic signature
|
</term>
is a set of
<term>
words
</term>
that
|
#6915
Given a particular concept, or word sense, atopic signature is a set of words that tend to co-occur with it. |
tech,19-3-P04-2005,bq |
NLP )
</term>
applications , such as
<term>
|
Word Sense Disambiguation ( WSD )
|
</term>
and
<term>
Text Summarisation
</term>
|
#6948
Topic signatures can be useful in a number of Natural Language Processing (NLP) applications, such asWord Sense Disambiguation ( WSD ) and Text Summarisation. |
tech,26-3-P04-2005,bq |
Sense Disambiguation ( WSD )
</term>
and
<term>
|
Text Summarisation
|
</term>
. Our method takes advantage of the
|
#6955
Topic signatures can be useful in a number of Natural Language Processing (NLP) applications, such as Word Sense Disambiguation (WSD) andText Summarisation. |
other,6-2-P04-2005,bq |
particular
<term>
concept
</term>
, or
<term>
|
word sense
|
</term>
, a
<term>
topic signature
</term>
is
|
#6911
Given a particular concept, orword sense, a topic signature is a set of words that tend to co-occur with it. |
other,8-1-P04-2005,bq |
approach for automatically acquiring
<term>
|
English topic signatures
|
</term>
. Given a particular
<term>
concept
|
#6901
We present a novel approach for automatically acquiringEnglish topic signatures. |
other,26-4-P04-2005,bq |
also exploits the large amount of
<term>
|
Chinese text
|
</term>
available in
<term>
corpora
</term>
and
|
#6984
Our method takes advantage of the different way in which word senses are lexicalised in English and Chinese, and also exploits the large amount ofChinese text available in corpora and on the Web. |
other,0-3-P04-2005,bq |
</term>
that tend to co-occur with it .
<term>
|
Topic signatures
|
</term>
can be useful in a number of
<term>
|
#6929
Given a particular concept, or word sense, a topic signature is a set of words that tend to co-occur with it.Topic signatures can be useful in a number of Natural Language Processing (NLP) applications, such as Word Sense Disambiguation (WSD) and Text Summarisation. |
lr,20-5-P04-2005,bq |
co-occurrence algorithm
</term>
on standard
<term>
|
WSD datasets
|
</term>
, with promising results . This paper
|
#7014
We evaluated the topic signatures on a WSD task, where we trained a second-order vector co-occurrence algorithm on standardWSD datasets, with promising results. |
lr,30-4-P04-2005,bq |
<term>
Chinese text
</term>
available in
<term>
|
corpora
|
</term>
and on the
<term>
Web
</term>
. We evaluated
|
#6988
Our method takes advantage of the different way in which word senses are lexicalised in English and Chinese, and also exploits the large amount of Chinese text available incorpora and on the Web. |