2019 3rd International Conference on Compute and Data Analysis (ICCDA 2019)
Тезисы до: 20.01.2019
Даты: 14.03.19 — 17.03.19
Область наук: Компьютерные;
Е-мейл Оргкомитета: firstname.lastname@example.org
Организаторы: ICCDA 2019
ACM--2019 3rd International Conference on Compute and Data Analysis (ICCDA 2019)--Ei Compendex, Scopus
ICCDA 2019, The 3rd International Conference on Compute and Data Analysis
University of Hawaii Maui College, USA
March 14-17 2019.
ICCDA 2019 is a not-to-be-missed opportunity that distills the most current knowledge on a rapidly advancing discipline in one conference. Join key researchers and established professionals in the field of Compute and Data Analysis as they assess the current state-of-the-art and roadmap crucial areas for future research.
We aim to building an idea-trading platform for the purpose of encouraging researcher participating in this event. The papers to be presented at ICCDA 2019 address many grand challenges in modern engineering. The full papers to be presented will be peer-reviewed by expert reviewers including the whole organising committees members.
We will be thankful for the contributions to ICCDA series. We look forward to your participation and continued engagement at future ICCDA conferences.
Accepted Papers (Full Paper) will be published in the International Conference Proceedings Series by ACM, which will be archived in the ACM Digital Library, and indexed by Ei Compendex, Scopus, and submitted to be reviewed by Thomson Reuters Conference Proceedings Citation Index (ISI Web of Science).
Northern Illinois University (NIU) DeKalb, USA, March 23-25, 2018
ICCDA 2018 papers published by ACM (ISBN 978-1-4503-6359-4)
Online in Xplore:https://dl.acm.org/citation.cfm?id=3193077.
Photos&more information,please refer to http://iccda.org/2018.html
Florida Polytechnic University, Lakeland, USA, May 19-23, 2017
Proceedings published by ACM (ISBN:978-1-4503-5241-3) has been online and indexed by EI&Scopus.
Online in Xplore:https://dl.acm.org/citation.cfm?id=3093241
Photos&more information,please refer to https://www.dropbox.com/sh/sshc9itlz0iid....
By Email: email@example.com
By Easy Chair: http://www.easychair.org/conferences/?co...
*Call for Papers:
General areas of interest to ICCDA include but are not limited to:
Mathematical, probabilistic and statistical models and theories
Machine learning theories, models and systems
Knowledge discovery theories, models and systems
Manifold and metric learning
Scalable analysis and learning
Heterogeneous data/information integration
Data pre-processing, sampling and reduction
Feature selection, transformation and construction
Large scale optimization
High performance computing for data analytics
Architecture, management and process for data science
Data analytics, machine learning and knowledge discovery
Learning for streaming data
Learning for structured and relational data
Latent semantics and insight learning
Mining multi-source and mixed-source information
Mixed-type and structure data analytics
Cross-media data analytics
Big data visualization, modeling and analytics
Relation, coupling, link and graph mining
Personalization analytics and learning
Web/online/social/network mining and learning
Cloud computing and service data analysis
Storage, retrieval and search
Data warehouses, cloud architectures
Information and knowledge retrieval, and semantic search
Web/social/databases query and search
Personalized search and recommendation
Human-machine interaction and interfaces
Crowdsourcing and collective intelligence
Ms. Maggie Lau
Tel: +86 1301 822222 0
Веб-сайт конференции: http://iccda.org/
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