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.
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
09月07日
2016
09月09日
2016
摘要截稿日期
注册截止日期
2015年09月02日 台湾-中国
2015 国际大数据科学理论,算法和应用研讨会
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