... build a MT evaluation metric for Chinese-
English translation with features selected from
above aspects.
3 A Regression SVM Approach Based on
Linguistic Motivated Features
Introducing machine ...
Following this intuition, from the plentiful lin-
guist information, we take the following factors in
to consideration:
● Content words are important to the semantic
meanin...
... judgments in training ex-
amples. Kulesza and Shieber (2004) raised two
main objections against regression for MT evalua-
tions. One is that regression requires a large set of
labeled training examples. ... classify its inputs; thus its outputs
are discrete. In contrast, a regression model learns
a continuous function that directly maps an input
to a continuous value. An MT ev...
... the positions of the LIRs in introns
and intergenic regions. A short distance to the exon–
intron boundary or transcription starting point is
an indication that an LIR is functioning in the gene.
A ... Ribonucleotide binding 0.01047 GO:0008092 Cytoskeletal protein binding 0.046358
GO:0031226 Intrinsic to plasma membrane 0.011022 GO:0005515 Protein binding 0.047541
A study on human l...
... tryptophans and tyrosines involved in
binding sites 1 and 2, respectively, are signified by yellow [41,42]. The conserved phenylalanine in CBM20 and invariant lysine in CBM21 are
shown in black inversion. ... Mutational
analysis of this site demonstrated a binding role [20].
Based on their sequences the starch-binding domains
(SBD) have also been classified into families of carbo-
h...
... a machine learning algorithm
for metonymy resolution. They state the problem
of metonymy resolution as a classification task be-
tween literal use of a word and a number of prede-
fined metonymy ... results.
4 Finding the Distance to the Typical
Context Set
The algorithm is intended to determine whether a
word (or an expression) in a given context is used
literaly or not.
As it was mentio...
... prediction model. The decision about
the representation is in turn divided into two sub-
questions: what features to select as input and
which type of value to assign to these features.
In most ... Some
reports on how automatic summarization can be
used to improve text categorization exist. For ex-
1
In terminology extraction all terms describing a domain
are to be extr...
... predicate/argument
pairs.
Once semantic representations are defined,
we need to design a kernel function to esti-
mate the similarity between our objects. As
suggested in Section 2 we can map them into
vectors in
n
and ... the sentence.
3.4 Comparison with Standard
Features
In this section we compare standard features
with the kernel based representation in order
to deriv...
... D385 in
PS1, indicated with ‘D’). This topology is also predicted by
HMMTOP2.1 without using constrained prediction. (B) Presenilin-like protein 2
(PSL2) (UniProt number Q8TCT8) has nine HRs (indicated ... N-ter-
minus could create an artificial TM region at the fusion
point, leading to incorrect localization of the reporter
gene. The contradicting results regarding the C-ter-
minal locati...
... prefixes for showing singular and plural, and cor-
responding prefixes to attach to adjectives and verbs.
For example, the prefixes for the class to which -toto
belongs are:
Singular Plural ... "child" as mtoto. In
our stem dictionary, however, we enter the stem toto and
the "normal form" nunua, rather than the stem nunu.
This is because the singular and plu...
... by constantly
changing contexts. Accordingly, the participants
were assigned to one of the experimental groups
and corresponding context condition already in the
second training phase that took ... organizations and loca-
tions – based on the eye-mind assumption. We
tested two main hypotheses – one relating to the
amount of contextual information being used for
annotation decisions,...