==== Proceedings will be published by IEEE and indexed by EI, SCI-indexed journal special issue opportunities ====
==== DSAA'2014 is in cooperation with ACM SIGKDD and technically co-sponsored by IEEE Computational Intelligence Society. ====
2014 IEEE International Conference on Data Science and Advanced Analytics (DSAA'2014)
30 October - 1 November, 2014, Shanghai, China
Website: http://datamining.it.uts.edu.
Important Dates
================
Paper Submission deadline: 5 July, 2014
Notification of acceptance: 10 August, 2014
Final Camera-ready papers due: 30 August, 2014
Submissions
============
https://www.easychair.org/
Publications
=============
All accepted papers will be published by the IEEE press and included in the IEEE Xplore Digital Library. The conference proceedings will be submitted for EI indexing through INSPEC by IEEE. Selected top quality papers after presented in the conference will be invited for extension and publication in the special issues of international journals, including IEEE Intelligent Systems, WWWJ, and Neurocomputing. The accepted workshop papers will be published through Springer CCIS series, which will also be indexed by EI.
Introduction
=============
Data driven scientific discovery approach has already been agreed to be an important emerging paradigm for computing in areas including social, service, Internet of Things (or sensor networks), and cloud. Under this paradigm, Big Data is the core that drives new researches in many areas, from environmental to social. There are many new scientific challenges when facing this big data phenomenon, ranging from capture, creation, storage, search, sharing, analysis, and visualization. The complication here is not just the storage, I/O, query, and performance, but also the integration across heterogeneous, interdependent complex data resources for real-time decision-making, collaboration, and ultimately value co-creation. Data sciences encompass the larger areas of data analytics, machine learning and managing big data. Data analytics has become essential to glean some understanding from large data sets and convert data into actionable intelligence. With the rapid growth in the vol
umes of data available to enterprises, Government and on the web, automated techniques for analyzing the data have become essential.
The 2014 IEEE International Conference on Data Science and Advanced Analytics (DSAA'2014) aims to provide a premier forum that brings together researchers, industry practitioners, as well as potential users of big data and advanced analytics, to promote collaborations and exchange of ideas and practices, discuss new opportunities, and investigate the best actionable analytics framework for wide range of applications. The conference solicits experimental and theoretical works on data science and advanced analytics along with their application to real life situations.
Topics of Interest
==================
General areas of interest to DSAA'2014 include but not Limited to:
Foundations
* New mathematical, probabilistic and statistical models and theories
* New learning theories, models and systems
* Deep analytics and learning
* Distributed and parallel computing (cloud, map-reduce, etc.)
* Non-iidness (heterogeneity & coupling) learning
* Invisible structure, relation and distribution learning
* Intent and insight learning
* Scalable analysis and learning
* Mining multi-source and mixed-source information
* Architecture, management and process
* Data pre-processing, sampling and reduction
* Feature selection and feature transformation
* High performance/parallel/
* Analytics architectures and infrastructure
* Heterogeneous data/information integration
* Crowdsourcing
* Human-machine interaction and interfaces
Retrieval, query and search
* Web/social web/distributed search
* Indexing and query processing
* Information and knowledge retrieval
* Personalized search and recommendation
* Query languages and user interfaces
Analytics, discovery and learning
* Mixed-type data
* Mixed-structure data
* Big data modeling and analytics
* Multimedia/stream/text/visual analytics
* Coupling, link and graph mining
* Personalization analytics and learning
* Web/online/network mining and learning
* Structure/group/community/
* Big data visualization analytics
* Large scale optimization
Privacy and security
* Security, trust and risk in big data
* Data integrity, matching and sharing
* Privacy and protection standards and policies
* Privacy preserving big data access/analytics
* Social impact
Evaluation, applications and tools
* Data economy
* Domain-specific applications
* Quality assessment and interestingness metrics
* Complexity, efficiency and scalability
* Anomaly/fraud/exception/
* Large-scale recommender and search systems
* Big data representation and visualization
* Post-processing and post-mining
* Large Scale Application Case Studies
* Online/business/government data analysis
* Mobile analytics for handheld devices
* Living analytics
Submission Guidelines
======================
Paper submissions should be limited to a maximum of seven (7) pages, in the IEEE 2-column format (see the IEEE Press Proceedings Author Guidelines: http://www.ieee.org/
Advisory Committee
===================
* Usama Fayyad ChoozOn Corporation, USA
* Masaru Kitsuregawa University of Tokyo, Japan
* Rao Kotagiri University of Melbourne, Australia
* Vipin Kumar University of Minnesota, USA
* Bengchin Ooi National University of Singapore
* Xin Yao University of Birmingham, UK
* Philip S Yu University of Illinois at Chicago, USA
Steering Committee
===================
* Longbing Cao University of Technology, Sydney, Australia
* Ming-Syan Chen Academia Sinica, Taiwan
* Diane J. Cook Washington State University
* Bart Goethals University of Antwerp, Belgium
* Herve Martin Laboratoire d'Informatique de Grenoble, France
* Hiroshi Motoda Osaka University and AFOSR/AOARD, Japan
* Jian Pei Simon Fraser University, Canada
* Vincent Tseng National Cheng kung University, Taiwan
* Geoff Webb Monash University, Australia
* Limsoon Wong National University of Singapore
* Osmar Zaiane University of Alberta, Canada
Organizing Committee
=====================
General Chairs
* Philip S Yu University of Illinois at Chicago, USA
* Masaru Kitsuregawa University of Tokyo
Conference Chairs
* Hiroshi Motoda Osaka University and AFOSR/AOARD, Japan
* Bart Goethals University of Antwerp, Belgium
* Minyi Guo Shanghai Jiaotong University, China
Program Committee Chairs
* Longbing Cao University of Technology, Sydney, Australia
* George Karypis University of Minnesota, USA
* Irwin King Chinese University of Hong Kong
* Wei Wang Fudan University, China
Local Arrangement Chairs
* Hongming Cai Shanghai Jiaotong University, China
* Wei Liu University of Technology, Sydney
Workshop Chairs
* Gang Li Deakin University, Australia
* Eric Gaussier Universit?Joseph Fourier, France
Tutorial Chairs
* Junbin Gao Charles Stuart University, Australia
* Sourav S Bhowmick Nanyang Technological University, Singapore
Panel Chairs
* Gabriella Pasi Universit?di Milano Bicocca, Italy
* Em-Ping Lim Singapore Management University, Singapore
Sponsorship Chairs
* Guangtao Xue Shanghai Jiaotong University, China
Publicity Chairs
* Xiaohui Tao University of Southern Queensland, Australia
* Xin Wang University of Calgary, Canada
* Xiaodong Yue Shanghai University
Registration/Finance Chairs
* Qi Gu Shanghai Jiaotong University, China
Publication Chair
* Frank Jiang University of Technology, Sydney, Australia
Technical Sponsors
===================
* ACM SIGKDD
* IEEE Computational Intelligence Society
* Springer
* IEEE Task Force on Data Sciences and Advanced Analytics
* IEEE NSW Section
* ACM SIGKDD Australia and New Zealand Chapter
Conference organizers
======================
* University of Technology Sydney, Australia
* Shanghai Jiaotong University, China
* Stanford University, USA
* University of Joseph Fourier, France
==== DSAA'2014 is in cooperation with ACM SIGKDD and technically co-sponsored by IEEE Computational Intelligence Society. ====
2014 IEEE International Conference on Data Science and Advanced Analytics (DSAA'2014)
30 October - 1 November, 2014, Shanghai, China
Website: http://datamining.it.uts.edu.
Important Dates
================
Paper Submission deadline: 5 July, 2014
Notification of acceptance: 10 August, 2014
Final Camera-ready papers due: 30 August, 2014
Submissions
============
https://www.easychair.org/
Publications
=============
All accepted papers will be published by the IEEE press and included in the IEEE Xplore Digital Library. The conference proceedings will be submitted for EI indexing through INSPEC by IEEE. Selected top quality papers after presented in the conference will be invited for extension and publication in the special issues of international journals, including IEEE Intelligent Systems, WWWJ, and Neurocomputing. The accepted workshop papers will be published through Springer CCIS series, which will also be indexed by EI.
Introduction
=============
Data driven scientific discovery approach has already been agreed to be an important emerging paradigm for computing in areas including social, service, Internet of Things (or sensor networks), and cloud. Under this paradigm, Big Data is the core that drives new researches in many areas, from environmental to social. There are many new scientific challenges when facing this big data phenomenon, ranging from capture, creation, storage, search, sharing, analysis, and visualization. The complication here is not just the storage, I/O, query, and performance, but also the integration across heterogeneous, interdependent complex data resources for real-time decision-making, collaboration, and ultimately value co-creation. Data sciences encompass the larger areas of data analytics, machine learning and managing big data. Data analytics has become essential to glean some understanding from large data sets and convert data into actionable intelligence. With the rapid growth in the vol
umes of data available to enterprises, Government and on the web, automated techniques for analyzing the data have become essential.
The 2014 IEEE International Conference on Data Science and Advanced Analytics (DSAA'2014) aims to provide a premier forum that brings together researchers, industry practitioners, as well as potential users of big data and advanced analytics, to promote collaborations and exchange of ideas and practices, discuss new opportunities, and investigate the best actionable analytics framework for wide range of applications. The conference solicits experimental and theoretical works on data science and advanced analytics along with their application to real life situations.
Topics of Interest
==================
General areas of interest to DSAA'2014 include but not Limited to:
Foundations
* New mathematical, probabilistic and statistical models and theories
* New learning theories, models and systems
* Deep analytics and learning
* Distributed and parallel computing (cloud, map-reduce, etc.)
* Non-iidness (heterogeneity & coupling) learning
* Invisible structure, relation and distribution learning
* Intent and insight learning
* Scalable analysis and learning
* Mining multi-source and mixed-source information
* Architecture, management and process
* Data pre-processing, sampling and reduction
* Feature selection and feature transformation
* High performance/parallel/
* Analytics architectures and infrastructure
* Heterogeneous data/information integration
* Crowdsourcing
* Human-machine interaction and interfaces
Retrieval, query and search
* Web/social web/distributed search
* Indexing and query processing
* Information and knowledge retrieval
* Personalized search and recommendation
* Query languages and user interfaces
Analytics, discovery and learning
* Mixed-type data
* Mixed-structure data
* Big data modeling and analytics
* Multimedia/stream/text/visual analytics
* Coupling, link and graph mining
* Personalization analytics and learning
* Web/online/network mining and learning
* Structure/group/community/
* Big data visualization analytics
* Large scale optimization
Privacy and security
* Security, trust and risk in big data
* Data integrity, matching and sharing
* Privacy and protection standards and policies
* Privacy preserving big data access/analytics
* Social impact
Evaluation, applications and tools
* Data economy
* Domain-specific applications
* Quality assessment and interestingness metrics
* Complexity, efficiency and scalability
* Anomaly/fraud/exception/
* Large-scale recommender and search systems
* Big data representation and visualization
* Post-processing and post-mining
* Large Scale Application Case Studies
* Online/business/government data analysis
* Mobile analytics for handheld devices
* Living analytics
Submission Guidelines
======================
Paper submissions should be limited to a maximum of seven (7) pages, in the IEEE 2-column format (see the IEEE Press Proceedings Author Guidelines: http://www.ieee.org/
Advisory Committee
===================
* Usama Fayyad ChoozOn Corporation, USA
* Masaru Kitsuregawa University of Tokyo, Japan
* Rao Kotagiri University of Melbourne, Australia
* Vipin Kumar University of Minnesota, USA
* Bengchin Ooi National University of Singapore
* Xin Yao University of Birmingham, UK
* Philip S Yu University of Illinois at Chicago, USA
Steering Committee
===================
* Longbing Cao University of Technology, Sydney, Australia
* Ming-Syan Chen Academia Sinica, Taiwan
* Diane J. Cook Washington State University
* Bart Goethals University of Antwerp, Belgium
* Herve Martin Laboratoire d'Informatique de Grenoble, France
* Hiroshi Motoda Osaka University and AFOSR/AOARD, Japan
* Jian Pei Simon Fraser University, Canada
* Vincent Tseng National Cheng kung University, Taiwan
* Geoff Webb Monash University, Australia
* Limsoon Wong National University of Singapore
* Osmar Zaiane University of Alberta, Canada
Organizing Committee
=====================
General Chairs
* Philip S Yu University of Illinois at Chicago, USA
* Masaru Kitsuregawa University of Tokyo
Conference Chairs
* Hiroshi Motoda Osaka University and AFOSR/AOARD, Japan
* Bart Goethals University of Antwerp, Belgium
* Minyi Guo Shanghai Jiaotong University, China
Program Committee Chairs
* Longbing Cao University of Technology, Sydney, Australia
* George Karypis University of Minnesota, USA
* Irwin King Chinese University of Hong Kong
* Wei Wang Fudan University, China
Local Arrangement Chairs
* Hongming Cai Shanghai Jiaotong University, China
* Wei Liu University of Technology, Sydney
Workshop Chairs
* Gang Li Deakin University, Australia
* Eric Gaussier Universit?Joseph Fourier, France
Tutorial Chairs
* Junbin Gao Charles Stuart University, Australia
* Sourav S Bhowmick Nanyang Technological University, Singapore
Panel Chairs
* Gabriella Pasi Universit?di Milano Bicocca, Italy
* Em-Ping Lim Singapore Management University, Singapore
Sponsorship Chairs
* Guangtao Xue Shanghai Jiaotong University, China
Publicity Chairs
* Xiaohui Tao University of Southern Queensland, Australia
* Xin Wang University of Calgary, Canada
* Xiaodong Yue Shanghai University
Registration/Finance Chairs
* Qi Gu Shanghai Jiaotong University, China
Publication Chair
* Frank Jiang University of Technology, Sydney, Australia
Technical Sponsors
===================
* ACM SIGKDD
* IEEE Computational Intelligence Society
* Springer
* IEEE Task Force on Data Sciences and Advanced Analytics
* IEEE NSW Section
* ACM SIGKDD Australia and New Zealand Chapter
Conference organizers
======================
* University of Technology Sydney, Australia
* Shanghai Jiaotong University, China
* Stanford University, USA
* University of Joseph Fourier, France
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