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[PVS] DMIN'09 - Deadline Extension

Deadline Extension 

              C A L L    F O R    P A P E R S

     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 
   Date and Location: July 13-16, 2009, Las Vegas, USA

The 2009 International Conference on Data Mining (DMINí09) 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! 

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.   

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

Special Session on Text and Web Mining
Organizer: Yanjun Li, Fordham University, yli@xxxxxxxxxxxxxxx
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.
Special Session on Real-World Data Mining Applications, Challenges, and Perspectives
Organizer: Mahmoud Abou-Nasr, Ford Motor Company Research and Innovation Center, mabounas@xxxxxxxx 
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
Special Session on Data Mining for Time Series Data - Forecasting, Classification and Clustering
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: n.kourentzes@xxxxxxxxxxxxxxx (alternatively please use s.crone@xxxxxxxxxxxxxxx) 
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.

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 revi!
 ewed 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. 
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:
Tutorial A: Data Mining with Sensitivity to Rare Events and Class Imbalance
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.
Tutorial B: Emerging Human-Web Interaction Research
Peter Geczy, National Institute of Advanced Industrial Science and Technology (AIST), Japan      
Date & Time: July 14, 2009 (6:00 - 8:00 pm) - tentative
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.
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.
The tutorial aims to approach a broad audience including, but not limited
- 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.
Tutorial C: Autonomous Machine Learning 
Asim Roy, Arizona State University    
Description: pending (preliminary announcement)

   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


General Enquiries: Robert Stahlbock 
General Conference Chair 
Programme Committee: Sven F. Crone
Conference Programme Co-Chair 
Student Funding Enquiries:  Stefan Lessmann
Student Chair & Conference Programm Co-Chair
Tutorials Session Proposals: Philippe Lenca
Tutorial Chair
Special Session Proposals: Gary M. Weiss
Special Session Chair
Exhibitors & Corporate Sponsors : Wolfram Lippe
Exhibit Chair