Call for papers Workshop on
INCREMENTAL CLASSIFICATION, CONCEPT DRIFT AND NOVELTY DETECTION [http://perso.rd.francetelecom.fr/lemaire/ICDM2013/] (IClaNov) In conjunction with INTERNATIONAL CONFERENCE ON DATA MINING (ICDM 2013, Dallas, Texas / December 8-11, 2013) [http://icdm2013.rutgers.edu/] Description: The development of dynamic information analysis methods, like incremental clustering, concept drift management and novelty detection techniques, is becoming a central concern in a bunch of applications whose main goal is to deal with information which is varying over time. These applications relate themselves to very various and highly strategic domains, including web mining, social network analysis, adaptive information retrieval, anomaly or intrusion detection, process control and management, recommender systems, technological and scientific survey, and even genomic information analysis in bioinformatics. The term “incremental” is often associated to the terms dynamics, adaptive, interactive, on-line, or batch. The majority of the learning methods were initially defined in a non incremental way. However, in each of these families, were initiated incremental methods making it possible to take into account the temporal component of a datastream. In a more general way incremental clustering algorithms and novelty detection approaches are subjected to the following constraints: - Possibility to be applied without knowing as a preliminary all the data to be analyzed; - Taking into account of a new data must be carried out without making intensive use of the already considered data; - Result must but available after insertion of all new data; - Potential changes in the data description space must be taken into consideration; - Independency of order of data arrival. This workshop aims to offer a meeting opportunity for academics and industry-related researchers, belonging to the various communities of Computational Intelligence, Machine Learning, Experimental Design and Data Mining to discuss new areas of incremental clustering, concept drift management and novelty detection and on their application to analysis of time varying information of various natures. Another important aim of the workshop is to bridge the gap between data acquisition or experimentation and model building. The set of proposed incremental techniques includes, but is not limited to: - Novelty and drift detection algorithms and techniques - Adaptive hierarchical, k-means or density based methods - Adaptive neural methods and associated Hebbian learning techniques - Multiview diachronic approaches - Probabilistic approaches like LDA or ICA-based approaches - Graph partitioning methods and incremental clustering approaches based on attributed graphs - Incremental clustering approaches based on swarm intelligence and genetic algorithms - Evolving classifier ensemble techniques - Dynamic features selection techniques - Object tracking techniques - Visualization methods for evolving data analysis results The list of application domain is includes, but it is not limited to: - Evolving textual information analysis - Evolving social network analysis - Dynamic process control and tracking - Dynamic scene analysis - Intrusion and anomaly detection - Genomics and DNA microarray data analysis - Adaptive recommender and filtering systems - Scientometrics, webometrics and technological survey All accepted workshop papers will be published in formal proceedings by the IEEE Computer Society Press. Important dates: - Paper submission: August 3, 2013 - Notification of acceptance: September 24, 2013 - Camera-ready: October 15, 2013 - ICDM 2013 Conference: December 8, 2013 Important - Submission Guidelines: - Please follow the regular submission guidelines of ICDM 2013 (paper submissions should be limited to a maximum of *8* pages) http://icdm2013.rutgers.edu/author-instructions Contact: [email protected] – [email protected] - [email protected], Organizing committee (tentative): - Abou-Nasr MahmoudFord Motor Company, USA - Al Shehabi Shadi Allepo University, Syria - Albatineh Ahmed N. Dept of Biostatistics Florida Int. U. Miami, USA - Alippi Cesare Politecnico di Milano, Italia - Allan James University of Massachusetts, USA - Arredondo Tomas U.T.F.S.M. Valparaíso, Chile - Athitsos Vassilis University of Texas, USA - Bennani Younes LIPN Paris, France - Bifet Albert University of Waikato, New Zealand - Bondu Alexis EDF R&D, France - Chiang Jung-Tsien University of Tainan, Taiwan - Chawla Nitesh Notre Dame University, Indiana, USA - Chen Chaomei Drexel University, Philadelphia, USA - Cuxac Pascal CNRS-INIST, Nancy, France - Diallo Abdoulaye B. UQAM Montreal Canada - Dror Gideon Academic college of Tel-Aviv, Yaffo, Israel - El Haddadi Anass IRIT, Toulouse, France - Escalante Hugo Jair National Institute of Astrophysics Optics and Electronics, Mexico - Estevez Pablo University of Santiago, Chile - Family Fazel National Research Council Ontario, Canada - García-Rodríguez José University of Alicante, Spain - Glanzel Wolfgang KU Leuven, Leuven, Belgia - Hammer Barbara University of Bielefeld, Germany - He Jing-Hao University of Rhode Island Kingston, USA - Kumova Bora I. Izmir University, Turkey - Kuntz-Cosperec Pascale Polytech'Nantes, France - Lallich Stephane University of Lyon 2, France - Lamirel Jean-Charles TALARIS- LORIA, Nancy, France - Lebbah Mustapha LIPN Paris, France - Lenca Philippe Telecom Bretagne, France - Lemaire Vincent Orange Labs, Lannion, France - Li Bin UTS, Sydney, Australia - Loosli Gaelle Polytech Clermont-Ferrand, France - Nuggent Rebecca Carnegie Mellon University, Pittsburgh, USA - Popescu Florin Fraunhofer Institute, Berlin, Germany - Pudi Vikram IIIT Hyderabad, India - Roveri Manuel Politecnico di Milano, Italia - Silver Danny University of Acadia, Wolfville, Canada - Smith Tony C. University of Waikato, Hamilton, New Zealand - Statnikov Alexander New York University, USA - Tamir Dan Texas State University, San Marcos USA - Torre Fabien University of Lille3, France - Kotzinos Dimitris ICS-Forth, Greece - Tseng Vincent University of Tainan, Taiwan - Vatsavai Ranga Raju Oak Ridge National Laboratory, USA - Zhou Zhi-Hua Nanjing University, China - Zhu Xingquan UTS, Sydney, Australia ---------------------------------------------- CLASS-L list. Instructions: http://www.classification-society.org/csna/lists.html#class-l
