Re: [ABE-L]: [ICDM 2009] Call for Papers: The 9th IEEE International Co

2009/5/12 Francisco Louzada-Neto <dfln@ufscar.br>

Prezados Pedro, Gauss e demais Colegas,

Na nova grade curricular do Bacharelado em Estatística da UFSCar, a qual entrou em vigor há 3 anos atras, tem uma disciplina específica sobre Mineração de Dados (DM). Ela está sendo ministrada este semestre pela 1a vez e eu sou o docente responsável pela mesma.

Concordo com vcs que precisamos continuar explorando a interface da Estatística com DM, a qual tem se apresentado como uma área interdisciplinar.

Como uma constatação empírica, a grande maioria dos nossos ex-alunos tem contato diário com grandes bancos de dados.
Acredito ser extremamente providencial a exposição de alunos do Bacharelado às metodologias de DM, mas também, conseguir que alunos do mestrado direcionem suas dissertações para o tema. Ultimamente temos alguns alunos trabalhando na área. Além de continuar induzindo pesquisas na área.

Quanto a divulgação de DM, alguns eventos, incluindo alguns promovidos pela ABE, tem aberto espaços. Com exemplo, Sinape 2000 (Mini-Curso sobre DM), Sinape 2008 (Sessão Temática), WFB 2009 (com várias conferências de pesquisadores importantes, incluindo o Prof. Gauss) e outros eventos acadêmicos, seminários e eventos direcionados ao mercado em que temos participado.

Quanto ao nosso Qualis, periódicos específicos importantes de DM não foram contemplados. Como o processo é evolutivo, acredito que em um futuro próximo isso poderá ser concretizar. Particularmente, a partir do momento em que começarmos a publicar na área.

Um gde abc,

Fco Louzada

gausscordeiro escreveu:

Caro Pedro e demais redistas,

Desculpem escrever sem acentos, mas a sua colocacao eh muito boa, principalmente,

a colocacao de debate sobre os currículos dos bacharelados e uma revisão das fronteiras e

interfaces como areas como 'data mining'.

Para seu conhecimento: participei e ajudei na formatacao inicial do WFB 2009 - Workshop

Franco Brasileiro sobre Mineracao de Dados -, no Centro de Informatica da UFPE na semana

passada, com a presenca de cerca de 100 pessoas (6 professores estrangeiros), e tive a

mesma impressao sua que alguns trabalhos sao, essencialmente, de conceitos e metodologia

da estatistica transfigurados num "framework" de computacao.

Estou muito longe de querer entrar nesta area - tenho problemas muito interessantes

para resolver na area que atuo -, mas estou ciente (superficialmente) das grandes potencialidades

de "data mining" no mundo atual.

Quem sabe se melhorarmos os curriculos nao aumentaremos a demanda de alunos para

o bacharelado em estatistica que, atualmente, eh muito baixa, por exemplo, comparada

com computacao. Assim, a chance de sucesso em garimpar um bom aluno em computacao

eh bem maior do que na estatistica, por conta da grande demanda do primeiro curso.

Saudacoes,

Gauss

"Nenhum trabalho de qualidade pode ser feito sem concentração e auto-sacrifício, esforço e dúvida" (Max Beerbohm).

<http://www.frasesfamosas.com.br/de/winston-churchill.html>

Em 12/05/2009 04:35, *Pedro Luis Nascimento Silva < pedronsilva@gmail.com >* escreveu:

Colegas, para conhecer.
Um comentário para animar a leitura: será que 'data mining' é o
'primo rico' da Estatística? A conferência abaixo descrita
certamente parece maior e mais 'rica' do que algumas conferências
clássicas da estatística... Só a lista de tópicos de interesse já
é boa leitura para ter idéia de quanta coisa de estatística tem na
conferência, mas a palavra estatística quase não aparece (contei
uma aparição de 'statistical').
Já que a discussão recente em nossa lista sugere revisão / debate
sobre currículos de nossos cursos, proponho que tal revisão não
deixe de examinar fronteiras e interfaces como esta da 'área' de
'data mining', onde parece que estamos diante de desafios e
oportunidades interessantes, mas que não parece que tenhamos sido
hábeis em explorar ou participar, ou de atrair para os espaços
usuais da estatística (SINAPE e outros eventos da ABE, revistas,
etc.).
Bom dia a tod@s <http://mce_host/compose?to=tod@s>.
Pedro.

*************************************************************
ICDM'09: The 9th IEEE International Conference on Data Mining
*************************************************************
Sponsored by the IEEE Computer Society

December 6-9, 2009
Miami, U.S.A.
http://www.cs.umbc.edu/ICDM09/

Important Dates
April 13, 2009 Deadline for Workshop Proposals
April 30, 2009 Deadline for ICDM Contest Proposals
June 26, 2009 Deadline for Paper Submission,
Tutorial Submission, and
Panel Proposals
July 7, 2009 Deadline for Exhibits and Demos Proposals
September 4, 2009 Notification to authors
September 28, 2009 Deadline for camera-ready copies
December 6-9, 2009 Conference

Call for Papers
***************
The IEEE International Conference on Data Mining (ICDM) has
established
itself as the world's premier research conference in data mining.
The 2009
edition of ICDM provides a leading forum for presentation of original
research results, as well as exchange and dissemination of innovative,
practical development experiences. The conference covers all
aspects of data
mining, including algorithms, software and systems, and
applications. In
addition, ICDM draws researchers and application developers from a
wide
range of data mining related areas such as statistics, machine
learning,
pattern recognition, databases and data warehousing, data
visualization,
knowledge-based systems, and high performance computing. By
promoting novel,
high quality research findings, and innovative solutions to
challenging data
mining problems, the conference seeks to continuously advance the
state-of-the-art in data mining. Besides the technical program, the
conference will feature workshops, tutorials, panels, and the ICDM
data
mining contest.

Paper Submissions
*****************
High quality papers in all data mining areas are solicited.
Original papers
exploring new directions will receive especially careful
consideration.
Papers that have already been accepted or are currently under
review for
other conferences or journals will not be considered for ICDM'09.

Paper submissions should be limited to a maximum of 10 pages in
the IEEE
2-column format, the same as the camera-ready format (see the IEEE
Computer
Society Press Proceedings Author Guidelines
http://www.ieeeconfpublishing.org/cpir/AuthorKit.asp?
Community=CPS&Facility=CPS_Dec&ERoom=ICDM+2008
<http://www.ieeeconfpublishing.org/cpir/AuthorKit.asp?Community=CPS&Facility=CPS_Dec&ERoom=ICDM+2008>).
All papers will be reviewed
by the Program Committee on the basis of technical quality,
relevance to
data mining, originality, significance, and clarity. A double
blind review
process will be adopted. Authors should avoid using identifying
information
in the text of the paper. A Submission Form to submit your work
will be
announced on the ICDM'09 website.

Accepted papers will be published in the conference proceedings by
the IEEE
Computer Society Press and accorded oral presentation times in the
main
conference. Submissions accepted as regular papers will be
allocated 10
pages in the proceedings. Submissions accepted as short papers will be
allocated 6 pages in the proceedings and will have a shorter
presentation
time at the conference than regular papers.

A selected number of IEEE ICDM'09 accepted papers will be invited for
possible inclusion, in expanded and revised form, in the Knowledge and
Information Systems journal published by Springer-Verlag.
*ICDM Best Paper Awards
**********************
IEEE ICDM Best Paper Awards will be conferred at the conference on the
authors of (1) the best research paper, (2) the best application
paper, and
(3) the best student paper. Strong, foundational results will be
considered
for the best research paper award and application-oriented
submissions will
be considered for the best application paper award. The best
student paper
award will be given to the authors of the best paper written
solely by one
or more students.

Workshops and Tutorials
***********************
ICDM'09 will host short and long tutorials as well as workshops
that focus
on new research directions and initiatives. All accepted workshop
papers
will be included in a separate workshop proceedings published by
the IEEE
Computer Society Press.

ICDM Data Mining Contest
************************
ICDM'09 will host a data mining contest to challenge researchers and
practitioners with a real practical data mining problem. For
further details
on proposals and _expression_ of interest, please see the Call for
Data Mining
Contest Proposals.

ICDM Exhibits and Demos
***********************
The ICDM'09 Exhibit and Demo section will consist of an Exhibit
Session and
a Demo Session. The Exhibit Session will offer opportunities to
distribute
product, service, and company literature, give demonstrations and
carry out
recruitment activities. The Demo Session will provide data mining
researchers and practitioners an exciting and highly interactive
way to
explore new ideas and results.

Topics of Interest
******************
* Data mining foundations
- Novel data mining algorithms in traditional areas (such as
classification, regression, clustering, probabilistic modeling,
pattern discovery, and association a nalysis)
- Models and algorithms for new, structured, data types, such as
arising in chemistry, biology, environment, and other scientific
domains
- Developing a unifying theory of data mining
- Mining sequences and sequential data
- Mining spatial and temporal datasets
- Mining textual and unstructured datasets
- Distributed data mining
- High performance implementations of data mining algorithms
- Privacy and anonymity-preserving data analysis
* Mining in emerging domains
- Stream data mining
- Mining moving object data, RFID data, and data from sensor networks
- Ubiquitous knowledge discovery
- Mining multi-agent data
- Mining and link analysis in networked settings: web, social and
computer networks, and online communities
- Mining the semantic web
- Data mining in electronic commerce, such as recommendation,
sponsored web search, advertising, and market ing tasks
* Methodological aspects and the KDD process
- Data pre-processing, data reduction, feature selection, and feature
transformation
- Quality assessment, interestingness analysis, and post-processing
- Statistical foundations for robust and scalable data mining
- Handling imbalanced data
- Automating the mining process and other process related issues
- Dealing with cost sensitive data and loss models
- Human-machine interaction and visual data mining
- Integration of data warehousing, OLAP and data mining
- Data mining query languages
- Security and data integrity
* Integrated KDD applications, systems, and experiences
- Bioinformatics, computational chemistry, eco-informatics
- Computational finance, online trading, and analysis of markets
- Intrusion detection, fraud prevention, and surveillance
- Healthcare, epidemic modeling, and clinical research
- Customer relationship management
- Telecommunications, network and systems management
- Sustainable mobility and intelligent transportation systems

Organizing Committee
********************
Conference Co-Chairs:
Sanjay Ranka, University of Florida
Philip S. Yu, University of Illinois at Chicago

Program Co-Chairs:
Hillol Kargupta, University of Maryland, Baltimore County
Wei Wang, University of North Carolina Chapel Hill

Steering Committee:
David J. Hand, Imperial College, London, UK
Ramamohanarao Kotagiri, University of Melbourne, Australia
Vipin Kumar, University of Minnesota, USA
Heikki Mannila, University of Helsinki, Finland
Gregory Piatetsky-Shapiro, KDnuggets, USA
Shusaku Tsumoto, Shimane University
Benjamin W. Wah, University of Illinois, Urbana-Champaign, USA
Xindong Wu (Chair), University of Vermont, USA
Philip S. Yu, IBM T.J. Watson Research Center, USA
Osmar R. Zaiane, University of Alberta

Local Arrangements Chair:
Tao Li, Florida International University

Finance Chair:
Vagelis Hristidis, Florida International University

Awards Committee:
James Bailey, University of Melbourne, Australia
Wei Fan, IBM T.J. Watson Research Center, USA
Minos N. Garofalakis, Technical University of Crete, Greece
Bart Goethals, University of Antwerp, Belgium
Jiawei Han (Chair), University of Illinois at Urbana-Champaign, USA
Hillol Kargupta, University of Maryland at Baltimore County, USA
Wei Wang, University of North Carolina at Chapel Hill, USA

Panels Chair:
Haym Hirsh, NSF and Rutgers

Workshop Co-Chairs:
Yucel Saygin, Sabanci University
Jeffrey Xu Yu, CUHK

Tutorials Chair:
Sanghamitra Bandyopadhyay, Indian Statistical Institute

ICDM Data Mining Contest Chair:
Qiang Yang, HKUST

Sponsorship Chair:
Gabor Melli, PredictionWorks

Publicity Chairs:
Ina Lauth, Fraunhofer IAIS (Europe)
Kun Liu, IBM Almaden Research Center (North America)

Exhibit and Demo Chairs
Kanishka Bhaduri, NASA Ames Research Center
LongBing Cao, University of Technology Sydney

Vice Chairs
Deepak Agarwal, Yahoo!
Charu Aggarwal,IBM T J Watson Research Center
Alok Choudhary,NWU
Diane Cook,Washington State University
Gautam Das,University of Texas at Arlington
Ian Davidson, University of California, Davis,
Robert Grossman, University of Illinois at Chicago
George Karypis, University of Minnesota
Ravi Kumar, Yahoo!
Ling Liu, Georgia Institute of Technology
Katharina Morik, University of Dortmund, Germany,
Olfa Nasraoui, University of Louisville
Srinivasan Parthasarathy, The Ohio State University
Jian Pei, Simon Fraser University
Naren Ramakrishnan, Virginia Tech
Rajeev Rastogi, Yahoo!, India
Ambuj Singh, UCSB
Shashi Shekhar, University of Minnesota
Kyuseok Shim, Seoul National University, Korea
Assaf Schuster, Technion
Myra Spiliopoulou, University of Magdeburg, Germany
Ashok Srivastava, NASA Ames Research Center
Jaideep Srivastava, University of Minnesota
Hannu Toivonen, University of Helsinki
Haixun Wang, IBM T.J. Watson Research Center
Carlo Zaniolo, UCLA
Osmar Zaiane, Univ of Alberta

Further Information
*******************
ICDM09@listserv.unc.edu <../../../undefined//compose?to=ICDM>
*
*

-- Pedro Luis do Nascimento Silva
Southampton Statistical Sciences Research Institute
University of Southampton
Phone: +44 23 80597169

*

Re: [ABE-L]: [ICDM 2009] Call for Papers: The 9th IEEE International Conference on Data Mining