... 9.71M 0.50M 9.45M 1.19M
4.1 Using a morphological tagger and
disambiguator
The split version of the corpus contains words
that are split into their stem and suffix forms by
using a previously developed ... 2
gives the total log-probability (using log
2
) for the
split and unsplit datasets using n-gram models
of different order. We compute the perplexity
of the two datasets using a common denomina-
tor: ... that using differing dependency offsets for
stems and suffixes can improve the perplexity.
345
which corresponds to a 27% improvement.
4.2 Separation of stem and suffix models
Only 45% of the words...
... (Schmid, 1994). 35 stopwords (quite fre-
quent words such as “be” and “have”) are removed
from the lexical network. Negation words include
33 words. In addition to usual negation words such
as “not” ... extracted
the words tagged with “Positiv” or “Negativ”, and
reduced multiple-entry words to single entries. As a
result, we obtained 3596 words (1616 positive words
and 1980 negative words)
1
. ... computation converged.
The words with high final average values are clas-
sified as positive words. The words with low final
average values are classified as negative words.
4.3 Hyper-parameter Prediction
The...
... classes. The words
belong to each class is called:
increasing -words, relatively constant -words, and
decreasing -words respectively.
Table 1 shows a sample of some classified
words according ... the words in each
group.
Table 1 Sample of Classified Words
Stability Class Example of words in each class
Increasing Words Sammy-Sosa, McGwire,
Carlos-Delgado
Relatively constant
words ... of
words frequency with time- series variation included
in both periods. The data of extracted words is shown
in Table 2.
In order to get the accuracy of the correct words that
are words...
... the
two words in that compound. Sets of compounds
from other sources would not have such associated
definitions. Second, by using compounds from
WordNet, we could guarantee that all constituent
words ... that the correct re-
lation between two words in a compound can be
deduced by finding other compounds containing
words from the same semantic categories as the
words in the compound to be disambiguated: ... obtained for that relation
from any other sense-pair, using the first term of
the score tuple as the main key for comparison
(lines 14 and 15), and using the second term as
a tie-breaker (lines 16...
... Similar Words
The contextually similar words of a word w are
words similar to the intended meaning of w in its
context. Below, we describe an algorithm for
constructing contextually similar words ... parsed corpus.
Attachment decisions are made using a
linear combination of features and low
frequency events are approximated using
contextually similar words.
Introduction
Prepositional phrase attachment ... the
contextually similar words of w. We retrieve
from the collocation database the words that
occurred in the same dependency relationship as
w. We refer to this set of words as the cohort of
w...
... rhyming words,
in WordSmith's rhyming dimension, for an unknown
word.
Z. Rhyme
The WordSmith rhyme dimension is based on two files.
The first is a main file keyed on the spelling of words ...
words. They also show how answer~ to these
psycholinguistic questions can, in turn, contribute to
282
USING AN ON=LINE DICTIONARY TO FIND RHYMING WORDS
AND PRONUNCIATIONS FOR UNKNOWN WORDS ... in the pronunciation of
known words (Rosson, 1985).
Until recently, it was generally assumed that novel
words or pseudowords (letter strings which are not real
words of English but which conform...
... number of words present in both C and
WN divided by N; (2) Precision*: the number of
correct words divided by N. Correct words are ei-
ther words that appear in the WN subtree, or words
whose ... manner, using meta-patterns comprised
of high frequency words and content words.
2. Identification of pattern candidates that give
rise to symmetric lexical relationships. This
is done using simple ... of
words present in both C and WN divided by the
number of (single) words in WN; (4) The num-
ber of correctly discovered words (New) that are
not in WN. The Table also shows the number of
WN words...
... POS
tags of unknown words. We propose a
probabilistic model for POS guessing of
unknown wordsusing global information
as well as local information, and estimate
its parameters using Gibbs sampling. ... estimated
using all the training data (Figure 2, *2). Local
3
A major method for generating such pseudo unknown
words is to collect the words that appear only once in a cor-
pus (Nagata, 1999). These words ... unknown
words whose lexical forms appear only once in
the training or test data, so we process only non-
unique unknown words (unknown words whose
lexical forms appear more than once) using the
proposed...
... Top
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... the
New File wizard.
Using GUI Templates
If you want to visually edit a Java GUI form using the IDE's GUI Builder, you
have to create the form's source file using the IDE's Java ... chunks of code for you.
This section covers the following topics:
■
Creating Java Files
■
Using File Templates
■
Using GUI Templates
■
Editing Java Files in the Source Editor
■
Code Completion
■
Code ... built using your
own Ant build script.
Free-form
project icon
Web Project with Existing Ant Script. Template for creating a
web project based on your own web and Java sources, built
using...
... of Books on Building Web Services Using .NET
Web Services Developer Center
This page lists books about Web services in general and about building
Web services using .NET in particular.
Located ... Assertions, and WS-Security Policy.
ã How to implement a policy framework using WSE 2.0.
ã How to implement role-based authorization using WSE and the WS-
Policy family of specifications. Authorization ... Overview and definition of secure conversation using WS-Secure
Conversation.
ã How to implement a secure conversation between a Web service and its
client, using a security token service provider....