Call for Papers

 

We invite original research articles, reviews, industry white paper, work in progress report, innovative concepts and thought paper in the focus areas listed below. Further, we invite submissions in related areas not restricted to the listed topics. Submissions are open to all practitioners, researchers, scholars, professionals from industry and government sectors.

This Conference uses double-blind review, which means that both the reviewer and author identities are concealed from the reviewers, and vice versa, throughout the review process.

Submitted papers should report original research work which has not been submitted elsewhere(conference or journal) and /or  undergoing review. Submitted paper should follow the IEEE conference  see https://www.ieee.org/conferences/publishing/templates.html and double column style and should be at most 5 pages in length.The submissions are handled only through the Easy chair website at: https://easychair.org/conferences/?conf=comitcon2019.

Machine Learning

  • Aspects of Data Mining
  • Association Rules
  • Automatic Semantic
  • Annotation of Media Content
  • Bayesian Models and Methods
  • Case-Based Reasoning and Learning
  • Classification and Model Estimation
  • Clustering and Its Applications
  • Data Stream Mining
  • Deep Learning
  • Fast Learning Methods
  • Feature Selection
  • Reduction and Learning
  • Frequent Pattern Mining
  • Goodness Measures
  • Inductive Learning
  • Inference Rule Learning
  • Machine Learning in AI
  • Information Retrieval
  • Learning and Adaptive Control
  • Real-Time Learning
  • Real-Time Event Learning and Detection
  • Selection with Small Samples
  • Similarity Measures and Learning of Similarity
  • Social Media Mining
  • Statistical and Evolutionary Learning
  • Statistical Learning and Neural Net Based Learning
  • Support Vector Machines
  • Text, Video and, Image Mining
  • Soft Computing
  • Time Series and Sequential Pattern Mining

Big Data

  • Big Data Analytics
  • Big Data Search and Mining
  • Machine Learning
  • Data Stream Mining
  • Text Mining
  • Statistical Modelling
  • Sentiment Analysis
  • Social Network Analysis
  • Visualization Analytics for Big Data
  • Data Acquisition
  • Integration, Cleaning, and Best Practices
  • Internet of Things (IoT)
  • Link and Graph Mining
  • Web Search and Mining
  • Natural Language Processing
  • Soft Computing
  • Big Data Search Architectures
  • Scalability and Efficiency
  • Big Data Applications
  • Big Data and Society
  • Critical Infrastructure Security
  • Data Privacy
  • Information Security

Cloud Computing

  • Cloud as a Service
  • Cloud Infrastructure
  • Cloud Management and Operations
  • Cloud Security
  • Cloud Computing Pricing and Economics
  • Cloud Computing in Business Intelligence
  • Cloud Performance, Scalability, and Reliability
  • Data Analytics in Cloud
  • Cloud Development and Its Applications

Parallel Computing

  • Multicore and Many-Core Systems
  • High-Performance Systems
  • Interconnection Networks
  • Energy Efficient Design
  • Performance Evaluation of Parallel Algorithms
  • Parallel Programming Languages
  • FPGA’s and GPGPU
  • Compilers in Parallel Environment
  • Stream Processors in GPU
  • Parallel Computing in Big Data Analytics
  • Virtual and Augmented Reality (VR and AR)
  • Robotics
  • Efficient Resource Utilization
  • Operating Systems and Middleware for Parallel Architecture
  • Parallel Methods for Deep Learning and AI Design Patterns for Parallel Computing
  • Parallel Sparse Matrix Computations
  • Load Balancing
  • Theoretical Studies on Parallel/Grid Computing
  • Novel System Architectures
  • Heterogeneous Systems
  • Real World Applications
  • High-Performance Computing
  • Software-Hardware Co-design