会議情報
BigData' 2015: ASE International Conference on Big Data
http://bigdata2015.scienceengineeringacademy.org/
提出日:
2015-07-28 Extended
通知日:
2015-08-21
会議日:
2015-10-07
場所:
Kaohsiung, Taiwan
年:
5
閲覧: 7756   追跡: 0   出席: 0

論文募集
The ASE International Conference on Big Data aims to bring together academic scientists, researchers and scholars to exchange and share their experiences and research results in Advancing Big Data Science & Engineering (BIGDATA). The phrase “big data” in this solicitation refers to large, diverse, complex, longitudinal, and/or distributed data sets generated from instruments, sensors, Internet transactions, email, video, click streams, and/or all other digital sources available today and in the future.

The current focus is to advance the core scientific and technological means of managing, analyzing, visualizing, and extracting useful information from large, diverse, distributed and heterogeneous data sets so as to: accelerate the progress of scientific discovery and innovation; lead to new fields of inquiry that would not otherwise be possible; encourage the development of new data analytic tools and algorithms; facilitate scalable, accessible, and sustainable data infrastructure; increase understanding of human and social processes and interactions; and promote economic growth and improved health and quality of life. The new knowledge, tools, practices, and infrastructures produced will enable breakthrough discoveries and innovation in science, engineering, medicine, commerce, education, and national security.

A long-term strategy to address various big data challenges, which include advances in core techniques and technologies; big data infrastructure projects in various science, biomedical research, health and engineering communities; education and workforce development; and a comprehensive integrative program to support collaborations of multi-disciplinary teams and communities to make advances in the complex grand challenge science, biomedical research, and engineering problems of a computational- and data-intensive world.

The conferences were held in Washington D.C. in 2012, in Orlando, Florida in 2013, and at Harvard University, Cambridge, MA in 2014. This year is the first time for the conference to be held outside USA. It will be hosted by National University of Kaohsiung, Taiwan from Oct. 7th to 9th, 2015, and held jointly with the Fourth ASE International Conference on Social Informatics.

Topics of particular interest include, but are not limited to:

    Big Data Science: Theories, models, algorithms, benchmarking, curation, and methods for understanding big data
    Big Data Computing: Infrastructures, tools, programming, architectures, benchmarking, and testing of big data systems using Map/Reduce, Hadoop and others
    Big Data Mining: Acquisition, representation, indexing, storage, management, processing, pre-processing and post-processing of big data
    Big Data Analytics: Metrics, frameworks, evaluation, tools, analysis, visualization of big data
    Big Data Understanding: learning, knowledge discovery, business and consumer intelligence, user behavior, community discovery
    Big Data Applications: Industrial and scientific applications of big data such as search, recommendations, business intelligence, marketing, social media, good practices and reproducibility.
    Big Data Privacy and Security: Data privacy enhancing technologies, privacy-preserving computing, risk analysis, modeling, and management, trustworthy computing, access control
最終更新 Dou Sun 2015-07-11
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関連仕訳帳
CCF完全な名前インパクト ・ ファクター出版社ISSN
cIEEE Transactions on Big DataIEEE2332-7790
Big Data Research3.578Elsevier2214-5796
Scientific DataSpringer2052-4463
BioData Mining2.522Springer1756-0381
ACM SIGMIS Database ACM0095-0033
Crisis Communications Springer2194-9794
International Journal of Mathematics and Mathematical SciencesHindawi0161-1712
Measurement and Control1.229SAGE0020-2940
cIntelligent Data Analysis0.691IOS Press1088-467X
Journal of Simulation1.533Taylor & Francis1747-7778
完全な名前インパクト ・ ファクター出版社
IEEE Transactions on Big DataIEEE
Big Data Research3.578Elsevier
Scientific DataSpringer
BioData Mining2.522Springer
ACM SIGMIS Database ACM
Crisis Communications Springer
International Journal of Mathematics and Mathematical SciencesHindawi
Measurement and Control1.229SAGE
Intelligent Data Analysis0.691IOS Press
Journal of Simulation1.533Taylor & Francis
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