... the algorithms and by not subdividing
the training words in word classes.
4 Generation of rules and look-up data
structure
4.1 Building a rule set from training pairs
The training algorithm ...
one of the remaining candidates instead.
The training pairs that are matched by the pat-
tern of the winning rule become the supporters
and non-supporters of that n...
... Automatic Detection of Grammar Elements that Decrease Readability
Masatoshi Tsuchiya and Satoshi Sato
Department of Intelligence Science and Technology,
Graduate School of Informatics, Kyoto University
tsuchiya@pine.kuee.kyoto-u.ac.jp, ... unreadable.
The goal of our study is to present tools that help
rewriting work of improving readability in Japanese.
The first tool is t...
... Effect of echinomycin on HIF-1a protein level. HepG2 and HeLa cells were incubated for 5 or 16 h under hypoxia or normoxia in the
presence or absence of increasing concentrations of echinomycin. ... effect is caused by an increase in HIF-1a pro-
tein level, resulting from an increase in the transcription of the HIF-1A
gene in the presence of a low concentration of echino...
... samples of words
serve as input to the training procedure.
In a treebank training step we observe for each
rule in the training grammar how often it is used
for the training corpus. The grammar rules ... want to examine the in-
fluence of the size of the training corpus on the
results of the evaluation. Therefore, we split the
training corpus into 9 corpora, where...
... adaptation of the rule set to new
domains and corpora.
1 Motivation
Information Extraction (IE) systems often face
the problem of distinguishing between affirmed,
negated, and speculative information in ... of phrases split
into subsets (preceding vs. following their scope) to
identify cues using string matching. The cue scopes
extend from the cue to the beginning or end of the
s...
... also that the dashed lines con-
necting placeholders of two texts (hypotheses) in-
dicate structurally equivalent nodes. For instance,
the dashed line between
3
and
b
links the main
verbs both in ... the point of
view of bag -of- word methods, the pairs (T
1
, H
1
)
and (T
1
, H
2
) have both the same intra-pair simi-
larity since the sentences of T
1
and H
1
as well as
t...
... sent ences in table.
We can predict that there are opinion sentences
in this table, because the left column acts as a
header and there are indicators (plus and minus)
in that column.
3.3 Linguistic ... Learning the polarity of words
There are some works that discuss learning the po-
larity of words instead of sentences.
Hatzivassiloglou and McKeown proposed a
method o...
... described in that paper.
The motivation for including the list of opin-
ion-bearing words as one of our features is that
pro and con sentences are quite likely to contain
opinion-bearing expressions ... sentence
in those reviews collected from each domain
with the features described in Section 3.1. We
divided the data for training and testing. We then
trained our mod...
... noting that
human translations are generally good and machine
translations poor, that binary training data can be
created by taking the human translations as posi-
tive training instances and ... for doing this, as we were
interested in the level of agreement of intuitive un-
derstanding of fluency. We instructed them also that
they should evaluate the sentence without co...
... Evaluation of Machine Translation Quality Using Longest Com-
mon Subsequence and Skip-Bigram Statistics
Chin-Yew Lin and Franz Josef Och
Information Sciences Institute
University of Southern ... using bag -of- words instead. Instead of
error measures, we can also use accuracy measures
that compute similarity between candidate and ref-
erence translations in proportion to t...