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"During the last decade robots have begun to permeate everyday life (robotic lawn mowers; floor cleaners, autonomous cars etc); equally, closely related technologies are beginning to permeate the military– already US naval sh...
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Ms Pac-Man vs Ghosts...
This year's Ms Pac-man vs Ghosts Competition is now open for submissions. The competition allows you to develop AI controllers for the classical arcade game Ms Pac-Man. However, this year the competition takes a unique look at the...
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AISB YouTube Channel
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New AISB Website
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AISB Website Beta
The AISB's new website is now gone beta. Some of the new features member's can look forward to enjoying will be better integration with the AISB LinkedIn group, frequent news updates, a new member's section and up-to-date AI med...
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Lighthill Debates
The Lighthill debates from 1973 are now available on YouTube. You need to a flashplayer enabled browser to view this YouTube video
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Notice
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 http://icdm08.isti.cnr.it 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 (http://www.cs.uvm.edu/~kais/) 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 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 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 (Ask.com, 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 ******************* icdm08-chair@isti.cnr.it icdm08-organizer@isti.cnr.it surface address: IEEE - ICDM08 KDD Lab, ISTI-CNR via A. Moruzzi, 1 56124 Pisa, Italy Phone: +39 050 3152999 - 3153000 - 3153001 Fax: +39 050 3152040 |



