other,31-1-H01-1040,bq |
- can be used to enhance access to
<term>
|
text
|
collections
</term>
via a standard
<term>
text
|
#305
In this paper we show how two standard outputs from information extraction (IE) systems - named entity annotations and scenario templates - can be used to enhance access totext collections via a standard text browser. |
tech,36-1-H01-1040,bq |
text collections
</term>
via a standard
<term>
|
text
|
browser
</term>
. We describe how this information
|
#310
In this paper we show how two standard outputs from information extraction (IE) systems - named entity annotations and scenario templates - can be used to enhance access to text collections via a standardtext browser. |
tech,38-3-H01-1040,bq |
increased potential of
<term>
IE-enhanced
|
text
|
browsers
</term>
. At MIT Lincoln Laboratory
|
#383
We also report results of a preliminary, qualitative user evaluation of the system, which while broadly positive indicates further work needs to be done on the interface to make users aware of the increased potential of IE-enhanced text browsers. |
other,11-7-H01-1042,bq |
six extracts of
<term>
translated newswire
|
text
|
</term>
. Some of the extracts were
<term>
|
#695
Subjects were given a set of up to six extracts of translated newswire text. |
other,20-2-P01-1008,bq |
translations
</term>
of the same
<term>
source
|
text
|
</term>
. Our approach yields
<term>
phrasal
|
#1798
We present an unsupervised learning algorithm for identification of paraphrases from a corpus of multiple English translations of the same source text. |
other,31-1-N03-1018,bq |
progressing from generation of
<term>
true
|
text
|
</term>
through its transformation into the
|
#2699
In this paper, we introduce a generative probabilistic optical character recognition (OCR) model that describes an end-to-end process in the noisy channel framework, progressing from generation of true text through its transformation into the noisy output of an OCR system. |
other,37-3-N03-1018,bq |
translation lexicons
</term>
from
<term>
printed
|
text
|
</term>
. We present an application of
<term>
|
#2782
We present an implementation of the model based on finite-state models, demonstrate the model's ability to significantly reduce character and word error rate, and provide evaluation results involving automatic extraction of translation lexicons from printed text. |
other,13-2-N03-2003,bq |
data
</term>
can be supplemented with
<term>
|
text
|
</term>
from the
<term>
web
</term>
filtered
|
#3041
In this paper, we show how training data can be supplemented withtext from the web filtered to match the style and/or topic of the target recognition task, but also that it is possible to get bigger performance gains from the data by using class-dependent interpolation of N-grams. |
other,24-1-N03-4010,bq |
answering capability
</term>
on
<term>
free
|
text
|
</term>
. The demonstration will focus on
|
#3660
The JAVELIN system integrates a flexible, planning-based architecture with a variety of language processing modules to provide an open-domain question answering capability on free text. |
lr,19-2-N03-4010,bq |
answer candidates
</term>
from the given
<term>
|
text
|
corpus
</term>
. The operation of the
<term>
|
#3681
The demonstration will focus on how JAVELIN processes questions and retrieves the most likely answer candidates from the giventext corpus. |
lr,1-3-P03-1050,bq |
training resources
</term>
. No
<term>
parallel
|
text
|
</term>
is needed after the
<term>
training
|
#4478
No parallel text is needed after the training phase. |
lr,0-4-P03-1050,bq |
phase
</term>
.
<term>
Monolingual , unannotated
|
text
|
</term>
can be used to further improve the
|
#4489
Monolingual, unannotated text can be used to further improve the stemmer by allowing it to adapt to a desired domain or genre. |
lr,26-6-P03-1050,bq |
affix lists
</term>
, and
<term>
human annotated
|
text
|
</term>
, in addition to an
<term>
unsupervised
|
#4560
Our resource-frugal approach results in 87.5% agreement with a state of the art, proprietary Arabic stemmer built using rules, affix lists, and human annotated text, in addition to an unsupervised component. |
other,16-7-P03-1050,bq |
average precision
</term>
over
<term>
unstemmed
|
text
|
</term>
, and 96 % of the performance of
|
#4586
Task-based evaluation using Arabic information retrieval indicates an improvement of 22-38% in average precision over unstemmed text, and 96% of the performance of the proprietary stemmer above. |
tech,3-1-C04-1116,bq |
smaller and more robust . We present a
<term>
|
text
|
mining method
</term>
for finding
<term>
synonymous
|
#6095
We present atext mining method for finding synonymous expressions based on the distributional hypothesis in a set of coherent corpora. |
|
aggregation system
</term>
using each author 's
|
text
|
as a coherent
<term>
corpus
</term>
. Our approach
|
#6133
This paper proposes a new methodology to improve the accuracy of a term aggregation system using each author's text as a coherent corpus. |
other,26-4-P04-2005,bq |
exploits the large amount of
<term>
Chinese
|
text
|
</term>
available in
<term>
corpora
</term>
and
|
#6985
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 the Web. |
lr,11-4-P04-2010,bq |
<term>
pronouns
</term>
in
<term>
unannotated
|
text
|
</term>
by using a fully automatic sequence
|
#7081
Furthermore, we present a standalone system that resolves pronouns in unannotated text by using a fully automatic sequence of preprocessing modules that mimics the manual annotation process. |
tech,24-5-P04-2010,bq |
open-domain question answering
</term>
and
<term>
|
text
|
summarisation
</term>
. In this paper , we
|
#7122
Although the system performs well within a limited textual domain, further research is needed to make it effective for open-domain question answering andtext summarisation. |
other,35-1-I05-4010,bq |
numbering system
</term>
in the
<term>
legal
|
text
|
hierarchy
</term>
. Basic methodology and
|
#8239
In this paper we present our recent work on harvesting English-Chinese bitexts of the laws of Hong Kong from the Web and aligning them to the subparagraph level via utilizing the numbering system in the legal text hierarchy. |