... Computational Linguistics
Using EmoticonstoreduceDependency in
MachineLearningTechniquesforSentiment Classification
Jonathon Read
Department of Informatics
University of Sussex
United Kingdom
j.l.read@sussex.ac.uk
Abstract
Sentiment ... optimised for use as sentiment classification
training data. 2,000 articles containing smiles and
2,000 articles containing frowns were held-out as
optimising test data. We took increasing amounts
of ... the remaining dataset (from 2,000
to 22,000 in increments of 1,000, an equal number
being taken from the positive and negative sets) as
optimising training data. For each set of training
data...
... per-
formances in this task (84.36% in test). There-
fore, we decided to adopt this as a basis in order
to get an automatic clause splitting tool for
Basque. But as it is known, machinelearning ... chunks to the beginning
and to the end of the sentence
number of nominal chunks to the begin-
ning and to the end of the sentence
number of subordinate-clause marks to
the beginning and to ... Spain.
{acpalloi,bertol,jipdisaa,jibizole,jipmaanm}@ehu.es
Abstract
In this paper, we describe the research
using machinelearningtechniquesto
build a comma checker to be integrated
in a...
... Patrick. 1993. Coding decision
trees. Machine Learning, 11:7–22.
Using MachineLearningTechniquesto Interpret WH-questions
Ingrid Zukerman
School of Computer Science and Software Engineering
Monash ... performance of our statistical models, includ-
ing the in uence of various training and testing
factors on predictive performance, and examine
the relationships among the informational goals.
In ... introduced a predictive model, built
by applying supervised machine- learning tech-
niques, which can be used to infer a user’s key in-
formational goals from free-text questions posed
to an Internet...
... in Example 8-9
.
Example 8-9. File: XPathQueryForm.cs
// Namespaces, variables, and constants
using System;
using System.Configuration;
using System.Windows.Forms;
using System.Text;
using ... Books Online under the
topics "Guidelines forUsing XPath Queries" and " ;Using XPath Queries."
In .NET, the DataSet is synchronized with the XmlDataDocument. As a result, in some ... System.Text;
using System.Xml;
using System.Data;
using System.Data.SqlClient;
// Table name constants
xmlNodeList[i].ChildNodes[3].InnerText +
Environment.NewLine + Environment.NewLine);
...
... candidate.
Finally, we use machinelearningtechniquesto
eliminate non-comparative sentences from the
candidates. As a result, we achieved signifi-
cant performance, an F1-score of 88.54%, in
our ... AFNLP
Extracting Comparative Sentences from Korean Text Documents Us-
ing Comparative Lexical Patterns and MachineLearningTechniques
Seon Yang
Department of Computer Engineering,
Dong-A ... is to find an effective method to
extract S1 and S2, but single-keyword searching
just outputs S1 and S3. In order to capture S2, we
added long-distance-words sequences to the set
of single-keywords....
... temporary exemptions to individuals
with injuries to the index fingers and permanent exemptions in cases where individuals are missing
index fingers. In Illinois, where retinal scanning was tested, ... errors in updating or deleting
demographic information, the general practice is to permit viewing of certain State information,
but to allow fundamental case changes in the State's database to ... the
Illinois Retinal Identification System (ISCAN).
Biometric Technology Retinal scanning (recently discontinued) and finger
imaging
Contractor(s) Printrak International, Inc., for finger imaging, and
EyeDentify,...
... domain X other
than it being a set. In order to study the problem of learning, we need
additional structure. In learning, we want to be able to generalize to unseen
data points. In the case of binary ... particu-
larly inmachine learning. Since these methods have a stronger mathematical
slant than earlier machinelearning methods (e.g., neural networks), there
is also significant interest in the statistics ... studied in
depth since they arise as covariance kernels of stochastic processes; see,
for example, Lo`eve [
93]. This connection is heavily being used in a subset
of the machinelearning community interested...
... intention
to capture, in this book, some of the latest advances in this emerging niche area.
Machine Learning Methods
Machine learning methods fall into the following broad categories: supervised learning, ... categories: supervised learning,
unsupervised learning, semi-supervised learning, analytical learning, and reinforcement
learning. Supervised learning deals with learning a target function from ... of developing and maintaining large and complex software systems
in a dynamic and changing environment, machinelearning methods have been playing an
increasingly important role in many software...
... from the training data. Then the prediction taking into account the
I Introduction to Dataset Shift
Dataset Shift inMachine Learning
Joaquin Qui˜nonero-Candela
Masashi Sugiyama
Anton Schwaighofer
Neil ... made major contributions to dealing with
dataset shift inmachine learning. Thanks to all of you for making this book happen!
Joaquin Qui˜nonero-Candela
Masashi Sugiyama
Anton Schwaighofer
Neil ... DATASET SHIFT IN
MACHINE LEARNING
EDITED BY JOAQUIN QUIÑONERO-CANDELA, MASASHI SUGIYAMA,
ANTON SCHWAIGHOFER, AND NEIL D. LAWRENCE
DATASET SHIFT INMACHINE LEARNING
QUIÑONERO-CANDELA,...
... criteria. Machinelearning af-
fords a unified framework to compose these crite-
ria into a single metric. In this paper, we have
demonstrated the viability of a regression approach
to learning the ... Brockett.
2001. A machinelearning approach to the automatic eval-
uation of machine translation. In Proceedings of the 39th
Annual Meeting of the Association for Computational Lin-
guistics, July.
Thorsten ... way to incorpo-
rate some assessment information into classification
training, we modify the parameter tuning process so
that SVM parameters are chosen to optimize for as-
sessment correlations in...
... chance for reaching a large number of rare pat-
terns. In future work we will try to exploit the web
as training resource for acquiring patterns while
using the parsed domain data as the source for ... Domain
Knowledge for Information Extraction. In Proc. of
COLING 2000, Saarbrücken, Germany.
R. Yangarber. 2003. Counter-training in the Discovery
of Semantic Patterns. In Proceedings of ACL-03, ... role infor-
mation is missing. E.g., in the management succes-
sion domain that concerns the identification of job
changing events, a person can either move into a
584
Step 1: (depicted in Figure...
... them being normal instances
and remaining 20 percent being anomaly instances. For NAD
2000 data set, we considered less number of instances i.e., 420
training instances and testing instances ... detecting attacks against
computer systems and networks, or against information
systems in general, as it is difficult to provide provably secure
information systems and maintain them in such ... methods applied into intrusion
detection [6], such as methods based on statistics, methods
based on data mining, methods based on machinelearning and
so on. In recent years, data mining technology...
... of the little things; look for
the smile
Finding Hot buttons
• Direct vs indirect
questions
• Writing down key
information
• What has failed for
them in the past?
Deliver for them!
Are buyers ... coaching clients who is
absolutely killing it!
• He left the Finance world to pursue his passion for
fitness, became a Personal Trainer in 2005.
• He went from being a BRAND new trainer to
opening ... loves selling personal training,
and loves showing other trainers how to get into
sales too.
Q & A Session
What questions or concerns do you
have?
What is your biggest concern
regarding sales?
What...
... Software
Accuracy
Baseline Transductive SVM Self-training
Co-training with random views Co-training and single classifier Co-training and combined classifier
Using 5% labeled data as training data
0.69
0.747
0.584
0.525
0.67
0.653
0.626
0.55
0.564
0.683
0.495
0.615
0.8675
0.7855
0.7
0.601
0.45
0.55
0.65
0.75
0.85
B
oo
k
D
VD
E
le
ctro
nic
K
itc
hen
H
ealt
h
N
etwor
k
P
et
S
oftwar
e
Accuracy
Using ... classification problem
in which labeled data in a domain are used to
train a domain-specific classifier. Pang et al.
(2002) are the first to apply supervised machine
learning methods tosentiment ... on Minimum Cuts. In
Proceedings of ACL-04.
Pang B., L. Lee, and S. Vaithyanathan. 2002. Thumbs
up? SentimentClassificationusingMachine
Learning Techniques. In Proceedings of
EMNLP-02....