AISB convention 2017

  In the run up to AISB2017 convention, I've asked Joanna Bryson, from the organising team, to answer few questions about the convention and what comes with it. Mohammad Majid al-Rifaie ( Tu...


Harold Cohen

Harold Cohen, tireless computer art pioneer dies at 87   Harold Cohen at the Tate (1983) Aaron image in background   Harold Cohen died at 87 in his studio on 27th April 2016 in Encintias California, USA.The first time I hear...


Dancing with Pixies?...

At TEDx Tottenham, London Mark Bishop (the former chair of the Society) demonstrates that if the ongoing EU flagship science project - the 1.6 billion dollar "Human Brain Project” - ultimately succeeds in understanding all as...


Computerised Minds. ...

A video sponsored by the society discusses Searle's Chinese Room Argument (CRA) and the heated debates surrounding it. In this video, which is accessible to the general public and those with interest in AI, Olly's Philosophy Tube ...


Connection Science

All individual members of The Society for the Study of Artificial Intelligence and Simulation of Behaviour have a personal subscription to the Taylor Francis journal Connection Science as part of their membership. How to Acce...



AISB event Bulletin Item

CFP: ICDM '08: The 8th IEEE International Conference on Data Mining

ICDM '08: The 8th IEEE International Conference on Data Mining
Sponsored by the IEEE Computer Society

December 15-19, 2008
 Pisa, Italy

Important Dates
 July 7, 2008          Deadline for paper submission
 September 15, 2008    Notification to authors
 October 7, 2008       Deadline for camera-ready copies
 December 15-19, 2008  Conference

Call for Papers

The IEEE International Conference on Data Mining series (ICDM) has
established itself as the world's premier research conference in data
mining, providing 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 '08.

A selected number of IEEE ICDM '08 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 and (2) the best application
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.

Workshops and Tutorials

ICDM '08 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

A call for organizing a data mining contest will be issued to
challenge researchers and practitioners with a real practical data
mining problem.

Topics of Interest

* Data mining foundations
 - Novel data mining algorithms in traditional areas (such as
   classification, regression, clustering, probabilistic modeling,
   pattern discovery, and association analysis)
 - Models and algorithms for new, structured, data types, such as
   arising in chemistry, biology, environment, and other scientific
 - 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 marketing tasks

* Methodological aspects and the KDD process
 - Data pre-processing, data reduction, feature selection, and
   feature transformation
 - Utility 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 for the KDD process
 - Visual analytics for 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, ecoinformatics
 - 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

Conference Co-chairs:

 Franco Turini (KDD Lab, Univ. Pisa, Italy)
 Carlo Zaniolo (UCLA, USA)
 Naren Ramakrishnan (Virginia Tech, USA)

Program Committee Chairs:

 Fosca Giannotti (KDD Lab, ISTI-CNR, Italy)
 Dimitrios Gunopulos (UC Riverside, USA)

Steering Committee Chair:

 Xindong Wu (Univ. Vermont, USA)

Tutorials Chairs:

 Dino Pedreschi (KDD Lab, Univ. Pisa, Italy)
 Arno Siebes (Uthrecht Univ., The Netherlands)

Workshops Chairs:

 Francesco Bonchi (KDD Lab, ISTI-CNR, Italy)
 Bettina Berendt (Humbolt Univ. Berlin, Germany)

Award Chair:

 Katharina Morik (Univ. Dortmund, Germany)

Panels Chair:

 Jean-Francois Boulicaut (INSA Lyon, France)

Exhibit and Demo Chairs:

 Haixun Wang (IBM T. J. Watson Research Center, USA)
 Michail Vlachos (IBM T. J. Watson Research Center, USA)

Publicity Chairs:

 Maurizio Atzori (KDD Lab, ISTI-CNR, Italy)
 Yan-Nei Law (Bioinformatics Institute, Singapore)

Sponsorship Chairs:

 Antonio Gulli (, Italy)
 Raffaele Perego (HPC Lab, ISTI-CNR, Italy)

Local Arrangements Chairs:

 Chiara Renso, Tiziana Mazzone (KDD Lab, ISTI-CNR, Italy)

Local Arrangements Team:  Miriam Baglioni, Michele Berlingerio,
Andrea Mazzoni,  Mirco Nanni, Ruggero Pensa, Fabio Pinelli,
Simone Puntoni, Salvatore Rinzivillo, Salvatore Ruggeri, Roberto
Trasarti (KDD Lab, Univ.Pisa and ISTI-CNR, Italy)

Finance Chair:

 Dino Pedreschi (KDD Lab, Univ. Pisa, Italy)

Further Information

surface address:
 via A. Moruzzi, 1
 56124 Pisa, Italy

 Phone: +39 050 3152999 - 3153000 - 3153001
 Fax: +39 050 3152040