Deadline Extension
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C A L L F O R P A P E R S
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The 5th International Conference on Data Mining 2009
DMIN'09 www.dmin--2009.com
part of
The 2009 World Congress in Computer Science,
Computer Engineering, and Applied Computing
(WORLDCOMP'09)
Date and Location: July 13-16, 2009, Las Vegas, USA
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The 2009 International Conference on Data Mining (DMINÂ’09) has extended its
deadline to receive papers until March 11, 2009 - so there is still time to
submitt! DMIN'09 has already received a large number of papers and will host
three special sessions, three tutorials (please see below for details) and a
large number of social events for networking ... So hurry up to ensure that you
do not miss out on this year's event!
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GENERAL TRACK SUBMISSIONS
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DMIN-09, the 5th International conference on data mining, is part of the 22
conferences held simultaneously from 13-16 July 2009 at the 2009 WORLDCOMP
conference, Monte Carlo Resort, Las Vegas, Nevada, USA. Topics of interest
include all aspects of data mining tasks, algorithms, integration, processes,
applications and systems - a comprehensive list may be found at the conference
website.
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SPECIAL SESSIONS SUBMISSIONS
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In addition to the main conference stream, you are invited to submitt your
paper to any of the three special sessions at DMIN'09 :
- Text and Web Mining
- Real-World Data Mining Applications, Challenges, and Perspectives, and
- Data Mining for Time Series Data - Forecasting, Classification and
Clustering.
The special sessions will be held during the DMIN conference. All papers for
the special sessions should be submitted using the standard procedures for DMIN
papers (see website), but the appropriate special session track should be
selected. Additional details for these three special sessions are provided
below and at http://www.dmin--2009.com/special_sessions.htm
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Special Session on Text and Web Mining
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Organizer: Yanjun Li, Fordham University, [email protected]
Text mining has been defined as 'the automated discovery of new, previously
unknown information by automatically extracting information from different
written resources.' Text mining operates on structured data from XML files or
unstructured or semi-structured data sets (such as email, full-text documents,
and HTML files). Text mining applications include information extraction, topic
tracking, summarization, categorization, clustering, concept linkage,
information visualization, and question answering. Web mining is the
application of data mining techniques to discover patterns from the World Wide
Web and includes web usage mining, web content mining, and web structure
mining. Web mining applications are in high demand since they can be used to
improve the effectiveness of search engines.
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Special Session on Real-World Data Mining Applications, Challenges, and
Perspectives
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Organizer: Mahmoud Abou-Nasr, Ford Motor Company Research and Innovation
Center, [email protected]
The past decade has witnessed a vast growth of the amount of data produced and
the proliferation of specialized databases in a wide range of business,
industrial, medical and scientific applications. Data mining is becoming an
increasingly important tool in the process of knowledge discovery and the
transformation of data into valuable information. The objective of this special
session is to provide a forum for the data mining researchers and industrial
practitioners to discuss data mining applications, issues, and the challenges
that arise when addressing real-world problems (e.g. dealing with highly skewed
data sets, massive and high dimensional data sets, non- stationary data,
unknown misclassification costs, lack of training data, missing and noisy data,
business process issues, etc.).
Topics of interest include, but are not limited to:
. Enterprise knowledge management/knowledge discovery
. Sales forecasting
. Automotive diagnostics
. Medical diagnostics
. Bioinformatics
. Challenges, including
o highly skewed data sets
o massive and high dimensional data sets
o non-stationary data
o unknown misclassification costs
o missing and noisy data
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Special Session on Data Mining for Time Series Data - Forecasting,
Classification and Clustering
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Organizers: Sven F. Crone & Nikolaos Kourentzes, Lancaster Centre for
Forecasting at the Department of Management Science, Lancaster University
Management School, UK, email for all enquiries: [email protected]
(alternatively please use [email protected])
This special session of DMIN'09 will cover all aspects of data mining for time
series data, particularly forecasting, classification and clustering of time
series.
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SUBMISSION OF PAPERS TO GENERAL TRACK AND SPECIAL SESSIONS:
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Prospective authors are invited to submit a draft paper in PDF format (up to 7
pages, standard double column IEEE style, single spaced, 10 pt font size,
margins left/right/bottom/top 0.75" (19 mm), first page top margin 1" (25 mm)),
to the DMIN'09 online paper submission system by Mar. 11, 2009. The link to the
online submission system will be available on the DMIN'09 website
(www.dmin--2009.com).
The length of the Camera-Ready papers (if accepted) will be limited to 7 (IEEE
style) pages. Papers must not have been previously published or currently
submitted for publication elsewhere. The first page of the draft paper should
include: title of the paper, name, affiliation, postal address, and email
address of each author as well as the name of the conference the paper is being
submitted to (i.e., DMIN'09). The first page should also identify the name of
the Contact Author and a maximum of 5 topical keywords that would best
represent the content of the paper.
To reflect upon feedback from last year we will extend the feedback given
within the review in aligning them with the IEEE guidelines for IJCNN and WCCI.
In particular, we aim at a fair, objective and transparent review process.
Therefore, we are publishing the review criteria to further support the reviews
provided (see www.dmin--2009.com). Papers will be evaluated for relevance to
DMIN, originality, significance, information content, clarity, and soundness on
an international level. Each aspect will be evaluated on a scale of 1 (bad -
reject) to 10 (excellent - accept) or 10%-100%. Papers need to achieve at least
50% overall score to be accepted without mandatory revisions. Each paper will
be refereed by at least two researchers in the topical area, and all reviews
are being considered for the acceptance/rejection decision. Each reviewer can
indicate their expertise and therefore their relative confidence in a
particular recommendation. The camera-ready papers will be reviewed by one
person.
We particularly encourage submissions of industrial applications and case
studies from practitioners. To reflect the requirements of an application or
project centric case study presentation, these will be subject to different
review criteria. In particular, they will not be evaluated using predominantly
theoretical research criteria of originality etc., but will take general
interest and presentation stronger into consideration. The camera-ready papers
will be reviewed by one person.
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TUTORIAL SESSIONS
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All tutorials are free to registered conference attendees of all conferences
held at WOLDCOMP'09. Those who are interested in attending one or more of the
tutorials are to sign up on site at the conference registration desk in Las
Vegas. A complete & current list of WORLDCOMP Tutorials can be found here.
In addition to tutorials at other conferences, DMIN'09 provides a set of
tutorials dedicated to Data Mining topics. The 2007 key tutorial was given by
Prof. Eamonn Keogh on Time Series Clustering. The 2008 key tutorial was
presented by Mikhail Golovnya (Senior Scientist, Salford Systems, USA) on
Advanced Data Mining Methodologies. This year DMIN will provide the following
tutorials:
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Tutorial A: Data Mining with Sensitivity to Rare Events and Class Imbalance
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Organizer: Nitesh V. Chawla, University of Notre Dame, USA
Recent years brought increased interest in applying data mining techniques to
difficult 'real-world' problems, many of which are characterized by imbalanced
learning data, where at least one class is much rarer relative to others.
Examples include (but are not limited to): fraud/intrusion detection, risk
management, medical diagnosis/monitoring, bioinformatics, text categorization
and personalization of information. The problem of imbalanced data is also
often associated with asymmetric costs of misclassifying elements of different
classes. Additionally the distribution of the test data may differ from that of
the learning sample and the true misclassification costs may be unknown at
learning time. Predictive accuracy, a popular choice for evaluating performance
of a classifier, will not be appropriate when the data is imbalanced and/or the
costs of different errors vary markedly.
This tutorial will introduce the problem of class imbalance, address the scope
of solutions available, present and contrast the appropriate metrics for
evaluating performance, and discuss the applications with case studies.
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Tutorial B: Emerging Human-Web Interaction Research
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Peter Geczy, National Institute of Advanced Industrial Science and Technology
(AIST), Japan
Date & Time: July 14, 2009 (6:00 - 8:00 pm) - tentative
Description:
World wide web has evolved from its earlier static form to an interactive
multimedia environment. Richness of interactions is rapidly approaching that of
the conventional stand-alone applications. Human interactivity with web-based
environments has been gaining increasing importance in both web research and
e-commerce. Mining and exploring human-web interactions bring numerous
challenges as well as opportunities. We will probe into the processes and
methods of human-web interaction research ranging from data acquisition
techniques, throughout analytics, to applications. Accounting for the latest
advances in the field, we will project the prospective future trends.
Objective:
The primary objective of the tutorial is to provide clear, yet reasonably
comprehensive, overview of the underlying principles, current approaches, and
potential future trends. Knowledge of the state-of-the-art in human-web
interaction research should be beneficial to a wide spectrum of individuals
studying, utilizing, designing, and/or managing web-based information systems.
Audience:
The tutorial aims to approach a broad audience including, but not limited
to:
- Students and Educators
- Academics and Researchers
- Practitioners and Managers
The topic shall be presented in an accessible and intuitive manner without
extensive technical details.
Short Bio:
Dr. Peter Geczy is a senior scientist at The National Institute of Advanced
Industrial Science and Technology (AIST). He also held positions at The
Institute of Physical and Chemical Research (RIKEN) and The Research Center for
Future Technology. His interdisciplinary scientific interests encompass domains
of human interactions and behavior in digital environments, information
systems, knowledge management and engineering, data and web mining, artificial
intelligence, and machine learning. His recent research focus also extends to
the spheres of service science, engineering, management, and computing. He
received several awards in recognition of his accomplishments. Dr. Geczy has
been serving on various professional committees, editorial boards, and has been
a distinguished speaker in academia and industry.
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Tutorial C: Autonomous Machine Learning
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Asim Roy, Arizona State University
Description: pending (preliminary announcement)
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IMPORTANT DATES
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March 11, 2009: Extended deadline for submission of papers (about 5 to 7
pages)
April 9, 2009: Notification of acceptance
May 1, 2009: Camera-Ready papers and Registration due
July 13-16, 2009: The 2009 International Conference on Data Mining (DMIN'09)
URL WORLDCOMP: http://www.world-academy-of-science.org/worldcomp09/ws
URL DMIN'09: http://www.dmin--2009.com
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CONTACT INFORMATION
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General Enquiries: Robert Stahlbock
General Conference Chair
[email protected]
Programme Committee: Sven F. Crone
Conference Programme Co-Chair
[email protected]
Student Funding Enquiries: Stefan Lessmann
Student Chair & Conference Programm Co-Chair
[email protected]
Tutorials Session Proposals: Philippe Lenca
Tutorial Chair
[email protected]
Special Session Proposals: Gary M. Weiss
Special Session Chair
[email protected]
Exhibitors & Corporate Sponsors : Wolfram Lippe
Exhibit Chair
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