DSAA 2014 - 2014 International Conference on Data Science and Advanced Analytics

The 2014 International Conference on Data Science and Advanced Analytics (DSAA'2014) aims to provide a timely 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 include, but are 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 distributed computing
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/network mining
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/change/event/crisis analysis
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
PUBLICATIONS
All accepted papers will be published by Springer through LNAI series. Selected top quality papers accepted and presented in the conference for extension and publication in the special issue of some international journals. The accepted workshop papers will be published through Springer CCIS series.