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WIBIG 2014 : Special Session on “Warehousing and Intelligent Analysis Of Complex Network Big Data” @DSAA2014 | |||||||||||
Link: http://datamining.it.uts.edu.au/conferences/dsaa14/ | |||||||||||
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Call For Papers | |||||||||||
Special Session on “Warehousing and Intelligent Analysis Of Complex Network Big Data (WIBIG 2014)” @DSAA'2014
Organizers Giuseppe Manco. ICAR-CNR, Italy, manco@icar.cnr.it Elio Masciari. ICAR-CNR, Italy, masciari@icar.cnr.it Domenico Saccà. Università della Calabria, Italy, domenico.sacca@unical.it Aim and Scope Nowadays, data generation has deeply changed with respect to last decades. In particular, data generated by web based system, government and companies exhibits a complex structure (e.g. multi-table data, XML data, web data, time series and sequences, graphs and trees, social network posts, tweets) that lead to a new paradigm of Big Data. This fact poses new challenges for current information systems for storing, managing and mining these complex data effectively. The aim of this special session is to bring together researchers and practitioners of data mining, data warehousing and data specialists who are interested in the advances and latest developments in this new area of modern computer science. It aims also at integrating recent results from existing fields such as data mining, statistics, machine learning and relational databases to discuss and introduce new algorithmic foundations and representation formalisms. We are interested in advanced techniques that while preserving the informative richness of data, allow us to efficiently and effectively identify complex information units present in such data. Topic of Interest WIBIG 2014 calls for international contributions related to foundations, challenges and research opportunities raised by real-world learning and data mining problems in which the data as well as patterns are complex and heterogeneous. The goal of the workshop is to promote and publish research in the field of complex pattern mining. Suggested topics include (but not limited to) the following: • Behavioural Analysis in Social Networks • Big Data Warehousing • Foundations on pattern mining, pattern usage, and pattern understanding • Mining stream, time-series and sequence data • Mining networks and graphs • Mining biological data • Mining dynamic and evolving data • Mining environmental and scientific data • Mining heterogeneous and ubiquitous data • Mining multimedia data • Mining multi-relational data • Mining semi-structured and unstructured data • Mining spatio-temporal data • Social Media Analytics • Ontology and metadata • Privacy preserving mining • Recommender Systems • Semantic Web and Knowledge Databases • Structured Output Prediction Submission Deadline Papers should be submitted by DSAA submission site choosing Special Session on “Warehousing and Intelligent Analysis Of Complex Network Big Data (WIBIG 2014)” before 22nd July 2014 (PST). Conference paper submissions should be limited to a maximum of seven (7) pages, in the IEEE 2-column format (see the IEEE Proceedings Author Guidelines: http://www.ieee.org/conferences_events/conferences/publishing/templates.html ). All submissions will be blind reviewed by the Program Committee on the basis of technical quality, relevance to conference topics of interest, originality, significance, and clarity. Author names and affiliations must not appear in the submissions, and bibliographic references must be adjusted to preserve author anonymity. Accepted conference papers will be published in the conference proceedings by IEEE and included into the IEEE Xplore Digital Library and will be submitted for EI indexing through INSPEC by IEEE. Program Committee • Saso Dseroski, Jozef Stefan Institute • Sergio Flesca, Università della Calabria • Pedro Furtado, Universidade de Coimbra • Joao Gama, University of Porto • Nada Lavrac, Jozef Stefan Institute • Barzan Mozafari, University of Michigan • Zbigniew Ras, University of North Carolina • Domenico Talia, Università della Calabria • Mohammed Zaki, Rensselaer Polytechnic Institute • Alicja Wieczorkowska, Polish-Japanese Institute of Information Technology • Carlo Zaniolo, UCLA |
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