Bigdata 2016 - 8th International Workshop on Theory, Algorithms and Applications of Big Data Science

Diverse multidisciplinary approaches are being continuously developed and advanced to address the challenges that Big Data research raises. In particular, the current academic
and professional environments are working to produce algorithms, theoretical advance in big data science, to enable the full utilisation of its potential, and better applications.
The proposed workshop focuses on the dissemination of original contributions to discuss and explore theoretical concepts, principles, tools, techniques and deployment models in the context of Big Data. In particular, via the contribution of both academics and industry practitioners, the current approaches for the acquisition, interpretation, and assessment of relevant information will be addressed in order to advance the
state-of-the-art Big Data technology.
Topics:
Contributions should focus on (but not limited to) the following topics:
Statistical and dynamical properties of Big Data;
Applications of machine learning for information extraction;
Hadoop and Big Data;
Data and text mining techniques for Big Data;
Novel algorithms in classification, regression, clustering, and analysis;
Distributed systems and cloud computing for Big Data;
Big Data applications;
Theory, applications and mining of networks associated with Big Data;
Large-scale network data analysis;
Data reduction, feature selection and transformation algorithms;
Data visualisation;
Distributed data analysis platforms;
Scalable solutions for pattern recognition;
Stream and real-time processing of Big Data;
Information quality within Big Data;
Threat detection in Big Data.