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. (7)
4 Extraction ofSemantic Orientation of
Words with Spin Model
We use the spinmodel to extract semantic orienta-
tions of words.
Each spin has a direction taking one of two values:
up or ... calculate values of
m with several different values of β and select the
value just before the phase transition.
4.4 Discussion on the Model
In our model, the semanticorientationsof words
are determined ... proposed a method for ex-
tracting semanticorientationsofwords with boot-
strapping. The semantic orientation of a word is
determined on the basis of its gloss, if any of their
52 hand-crafted rules...
... orienta-
tions of phrases as well as classification
methods based on the models. Although
each phrase consists of multiple words, the
semantic orientation of the phrase is not a
mere sum of the orientations ... of phrases depend on context just
as the semanticorientationsofwords do, but we
would like to obtain the most basic orientations of
phrases. We believe that we can use the obtained
basic orientations ... orientationsof phrases for affect analysis of
higher linguistic units such as sentences and doc-
uments.
The semantic orientation of a phrase is not a
mere sum of its component words. Semantic
orientations...
... ExtractingSemantic Roles from a Modelof Eventualities
Sylvie Ratt6
Universit6 du Qu6bec fi MontrSal / Linguistics ...
perceived instigator of the action).
Since one of the desired characteristic of a
roles system is the power to discriminate events
[5] (another "desired" property being to offer an
easier ... property being to offer an
easier selection of grammatical functions), the
recognition ofsemantic roles should be linked to
the interpretation of the event, that is to their dy-
namic properties....
... Robust Part -of- Speech Tagging Using Dynamic Model Selection
Jinho D. Choi
Department of Computer Science
University of Colorado Boulder
choijd@colorado.edu
Martha Palmer
Department of Linguistics
University ... tagging
accuracies of all tokens and unknown tokens, re-
spectively. Our individual models (Models D and
G) give comparable results to the other systems.
Model G performs better than Model D for BC, ... generalized model shows its
strength in tagging data that differs from the train-
ing data. The dynamic model selection approach
(Model S) shows the most robust results across gen-
res, although Models...
... analysis of text (CHEAT). Proceed-
ings of the PASCAL Challenges Workshop on Un-
supervised Segmentation ofWords into Morphemes,
Venice, Italy.
M. Creutz. 2006. Induction of the Morphology of Nat-
ural ... order model whereas
PROMODES-H is a novel development of PRO-
MODES with a higher order model. For both
algorithms, we defined the mathematical model
and performed experiments on language data of
the ... net increase of
0.0819 of correct boundaries which led to the in-
creased recall. Since the deduction of precision
is less than the increase of recall, a better over-all
performance of PROMODES-H...
... direction of research appeared in the
last decade, taking full advantage of the ”wisdom of
crowds” (Surowiecki, 2004). In simple words, wis-
dom of crowds enables parallel acquisition of opin-
ions ... same
number of head nods as the actual listener. See Fig-
ure 1 for a graphical representation of CRF model.
CRF Mixture of Experts To show the importance
of latent variable in our Wisdom-LMDE model, ... graphical
representation of a CRF Mixture of experts is given
in the Figure 1.
Actual Listener (AL) Classifiers This baseline model
consists of two models: CRF and LDCRF chains
(See Figure 1). To train these models,...
... Okumura.
2005. Extractingsemanticorientationsofwords using
spin model. In ACL’05, pages 133–140.
Peter Turney and Michael Littman. 2003. Measuring
praise and criticism: Inference ofsemantic orientation
from ... polar atoms. Takamura et al. (2005)
proposed usingspin models for extracting seman-
tic orientation of words. They construct a network
of wordsusing gloss definitions, thesaurus and co-
occurrence ... semantic orientation of for-
eign words. Identifying the semantic orienta-
tion ofwords has numerous applications in the
areas of text classification, analysis of prod-
uct review, analysis of...
... conditions, and
again using all of the joining terms produced the
best results.
The SVM algorithm produced the best accuracy
of all, achieving 50.1% accuracy using the com-
bined set of joining terms. ... on the task of map-
ping from a vector of web frequencies of para-
phrases containing joining terms to semantic rela-
tions. Secondly, we wanted to discover whether the
frequency of joining terms ... accuracy of 45.7%, where we achieve a
maximum accuracy of 38.1% on this dataset using
a nearest neighbor algorithm. However, their tech-
nique uses the cosine of the angle between the vec-
tors of...
... Number of correct words extracted by (DT)
Precision =
Total number ofwords extracted by (DT)
Number of correct words extracted by DT)
Recall =
❈
❈
❈
❈
❈
❈
Total number of correct words ...
classes of the input analysis data (test data).
2. POPULARITY OFWORDS
CONSIDERING TIME-SERIES
VARIATION
2.1 Stability Classes of the Words:
To judge the index of popularity ofwords with ...
divided by the total frequencies of the words in each
group.
Table 1 Sample of Classified Words
Stability Class Example ofwords in each class
Increasing Words Sammy-Sosa, McGwire,
Carlos-Delgado...
... get rid of these notes, please order your copy of ePrint 5.0 now.
VNU Journal of Science, Foreign Languages 25 (2009) 165-173
165
Grammatical and semantic features of some English words
and ...
subtle nuance of meaning in terms of grammar
and semantics. In this article, we are to discuss
the grammatical features [1,2] and semantic
structures [3-5] of the English words and
idioms ... (adv).
Semantically, ‘elated’ is specific and
formally used to describe a very high level of
‘delight’. It can also contain an idea of triumph.
In other words, it denotes the property of
feeling...
... demon-
strate the benefit of integrating opinion ex-
traction and polarity classification into a joint
model using features reflecting the global po-
larity structure. The model is trained using
large-margin ... Model
To train the model – find w – we applied max-margin
estimation for structured outputs, a generalization of
the well-known support vector machine from binary
classification to prediction of ... expressions (DSEs)
are explicit mentions of opinion whereas expressive
subjective elements (ESEs) signal the attitude of the
speaker by the choice of words. Opinions have two
features: polarity...