Department of Computer Science & Engineering of College of Engineering, Guindy is organizing an International Conference on Data Science Analytics and Applications (DaSAA 2016) which will provide a platform for Researchers, Engineers, Scientists and Academicians as well as Industrial Professionals all over the globe to present their innovative research ideas and developmental activities in data science analytics and applications. DaSAA 2016 is unique in itself due its focus on the recent developments in the Data Science Analytics and Applications, which will help the scientific community to exchange their experiences from their respective fields and to grow together.
Data collecting in various applications such as social network analysis, telecommunications, biology, health-care, cloud and decision making process concern large volume, complex, growing data sets with structured and un-structured data sources which in turn require Bulk processing in terms of terabytes to petabytes. With the fast development of networking, data storage, and the data collection capacity Data Science is now rapidly expanding in areas like social, service, Internet of Things, sensor networks etc. Thus Data Analytics has become essential for deeper understanding from large data sets and convert them into actionable intelligence to make better decision making for companies and organizations.
It is our great pleasure to invite you to participate in the International Conference on Data Science Analytics and Applications (DaSAA 2016), which will be held in College of Engineering Guindy, Anna University, Chennai-25, INDIA, between 7th and 9th December 2016, with pre-conference tutorial on 6th December, 2016.
It is planned to publish the proceedings with Springer in their Communications in Computer and Information Science series (Received conditional acceptance).
CCIS is abstracted/indexed in DBLP, Google Scholar, EI-Compendex, Mathematical Reviews, SCImago, Scopus.
♣ New mathematical, probabilistic and statistical models and Scalable analysis and learning
♣ High dimensional data, feature selection, feature transformation
♣ High performance computing for data science analytics
♣ Learning for streaming data, structured, Semi structured and Unstructured
♣ Mining heterogeneous source information
♣ Cross-media data analytics
♣ Big data modeling ,analytics and visualization
♣ Multimedia/stream/text/visual analytics
♣ Personalization analytics and learning
♣ Web/online/social/network mining and learning
♣ Structure/group/community/network mining
♣ Cloud computing and service data analysis
♣ Data warehouses, cloud architectures
♣ Large-scale databases and data structures
♣ Information and knowledge retrieval, and semantic search
♣ Query and search
♣ Personalized search and recommendation
♣ Human-machine interaction and interfaces
♣ Crowdsourcing
♣ Security and risk management
♣ Data integrity, matching and provisioning
♣ Privacy preserving for data access/analytics
12月07日
2016
12月09日
2016
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