ICCDA--ACM, Ei, Scopus 2020 : ACM--2020 The 4th International Conference on Compute and Data Analysis (ICCDA 2020)--Ei Compendex, Scopus

ACM--2020 The 4th International Conference on Compute and Data Analysis (ICCDA 2020)--Ei Compendex, Scopus
International Technological University, USA, in Silicon Valley, San Jose.
March 9-12, 2020.


The International Conference on Compute and Data Analysis (ICCDA), is an anual conference hold each year in United States. It is an international forum for academia and industries to exchange visions and ideas in the state of the art and practice of compute and data analysis.
The previous edition of ICCDA was held in Florida Polytechnic University, Lakeland, Northern Illinois University (NIU) DeKalb and University of Hawaii Maui College, Kahului .The ICCDA 2020 conference will be located in International Technological University, USA, in Silicon Valley, San Jose.
We will be thankful for the contributions to ICCDA series. We look forward to your participation and continued engagement at future ICCDA conferences.

*Conference Proceedings
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).


*Conference History
ICCDA 2019
University of Hawaii Maui College, Kahului,USA, March 14-17, 2019.
ICCDA 2019 papers published by ACM (ISBN:978-1-4503-6634-2)
Online in Xplore: http://dl.acm.org/citation.cfm?id=3314545
Photos&more information,please refer to http://iccda.org/2019.html


ICCDA 2018
Northern Illinois University (NIU) DeKalb, USA, March 23-25, 2018
ICCDA 2018 papers published by ACM (ISBN 978-1-4503-6359-4) has been online and indexed by EI&Scopus.
Online in Xplore:https://dl.acm.org/citation.cfm?id=3193077.
Photos&more information,please refer to http://iccda.org/2018.html


ICCDA 2017
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 http://iccda.org/2017.html


*Submission
By Email: [email protected]
By Easy Chair : http://www.easychair.org/conferences/?conf=iccda2020


*Venue:
International Technological University, USA
Silicon Valley, San Jose
Address:2711 N 1st St, San Jose, CA 95134
website:https://www.itu.edu


*Call for Papers:
Topics are interested but not limited to:

Foundations
Mathematical, probabilistic and statistical models and theories
Machine learning theories, models and systems
Knowledge discovery theories, models and systems
Manifold and metric learning
Deep learning
Scalable analysis and learning
Non-iidness learning
Heterogeneous data/information integration
Data pre-processing, sampling and reduction
Dimensionality 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
Multimedia/stream/text/visual analytics
Relation, coupling, link and graph mining
Personalization analytics and learning
Web/online/social/network mining and learning
Structure/group/community/network mining
Cloud computing and service data analysis

Storage, retrieval and search
Data warehouses, cloud architectures
Large-scale databases
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


*Contact:
Ms. Maggie Lau
Email: [email protected]
Tel: +86 1301 822222 0
http://iccda.org/