ACM--2018 The 2nd International Conference on Compute and Data Analysis (ICCDA 2018)--Ei Compendex, Scopus, and ISI

ICCDA 2018 The 2nd International Conference on Compute and Data Analysis
Northern Illinois University (NIU) DeKalb, USA, March 23-25, 2018.  
<ACM-Ei Compendex, Scopus>

ICCDA 2018 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 2018 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. 

*Proceedings:
Conference 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).

*Keynote speaker:
Prof. Anu Gokhale,Illinois State University, USA;
Prof. Shigang Chen, Department of Computer & Information of Science & Engineering University of Florida, USA;
Prof. Sen Zhang, Department of Math, Computer Science and Statistics State University of New York College at Oneonta, NY, United States;
Assoc. Prof. Donald S. Zinger,Northern Illinois University, USA.

*Submission:
By Email:  [email protected]:
By Easy Chair: https://easychair.org/conferences/?conf=iccda2018

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

*Call for Paper:
General areas of interest to ICCDA include but are 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

Others Details

For more details and updates please visit conference website