Special Sessions
SS13-Advance Computing Foundations, Techniques and Mathematical Models in Big Data, Machine Learning and Artificial Intelligence
Session Chair/ Session Organizers:
Dr. Praveen Kumar Bhanodia, Professor, Computer Science Engineering, Acropolis Institute of Technology & Research Indore India
Dr. Narendra Pal Singh Rathore, Associate Professor, Computer Science Engineering, Acropolis Institute of Technology & Research Indore India
Objective
The objective of the session is to provide a platform where researchers and experts can discuss and share their experiences pertaining to current and new research trends in the field of machine learning and artificial intelligence. It provides a platform where researchers, academicians, scholars and professionals present and discuss the recent advancement in the domain machine learning.
As the area of machine learning and artificial intelligence is broad and of interdisciplinary nature which includes mathematical computations, computer science and information processing, biomedical, psychology, etc. Thus, this session seeks contributions fromintelligent data processing perspective.
Authors may submit their genuine research work to the session which includes a large spectrum of topics including technical details, applications and implementation of machine learining, data mining and artificial intelligenence techniques.
Topics of the Special Session
The contribution may include the topics of interest, but are not limited to the topics mentioned below
• Big data analytics
• Data mining algorithms for Big data
• Deep Learning and its applications
• Applying machine learning in the area of healthcare, social media, bioinformatics.
• Data Mining, Data Science and Big Data
• Data Warehouse, Clustering, Visualization
• Graph Mining
• Data Security and Privacy
• Information Retrieval, Knowledge Discovery, Integration, Transformation
• Data Classification, Regression, Cleaning
• Social network and social media analysis
• Biomedical and Bioinformatics data analysis
• Neural Network and Deep Neural Networks
• Issues and challenges in intelligent data mining
• Analysis and Design of Algorithms
• Design issues in pattern recognition
• Artificial intelligence in Healthcare and Agriculture