International Conference on Data Mining, Data Science and Big Data 2015

Key Topics

• Data Science
  • Big Data Issues and Applications
  • Mathematical Issues in Data Science
  • Big Data in Smart Campus and Its Analization
  • Educational Data Science
  • Business data
  • Methods for analyzing Scientific Data
  • Recommender Systems
  • Social Network Analysis
  • Data Sciences with Text and Language
  • Data Quality and Data Preparation
  • Social Network Analysis
  • Data Sciences with Location
  • Mining Sequences
  • Data-driven Scientific Research
  • Evaluation and Measurement in Data Science
  • Large-scale Machine Learning Systems
  • Case Study of Data Science
  • Big Data Mining and Knowledge Management
  • Social impacts of Data Science
• Data Mining
  • Time series forecasting
  • Regression/Classification
  • Deviation and outlier detection
  • Segmentation/Clustering/Association
  • Web mining
  • Explorative and visual data mining
  • Mining large scale data
  • Mining text and semi-structured data
  • Multimedia mining (audio/video)
  • Temporal and spatial data mining
  • Mining large scale data/big data
  • Data Mining Algorithms
  • Data and knowledge representation
  • Distributed and grid based data mining
  • Engineering Mining
  • Business/Corporate/Industrial Data Mining
  • Integration of prior/domain knowledge
  • Data warehousing and OLAP integration
  • Data Mining Integration and Process
  • Data cleaning and preparation
  • Attribute discretisation and encoding
  • Feature selection and transformation
  • Missing value imputation
  • Sampling and rebalancing
  • Induction principles
  • Model selection/assessment and comparison
  • Model interpretation
  • Security Data Mining
  • Data Mining Applications
  • Efficient and distributed data mining platforms and algorithms
• Big Data
  • Techniques and models for Big Data
  • Big Data Computing and Service
  • Big Data Modeling, Sharing Technologies and Platforms
  • Algorithms and systems for Big Data
  • Big Data in Smart Campus and Its Analization
  • Big Data Analytics and Social Media
  • Big Data Mining and Knowledge Management
  • Parallel and Distributed Computing for Big Data
  • Machine Learning and AI for Big Data
  • Big Data Intelligence and Knowledge Engineering
  • Databases and Data Mining for Big Data
  • Hardware/Software Infrastructure for Big Data
  • Security and Privacy for Big Data
  • Big Data Centre and Enable Technologies
  • Large-scale machine learning systems
  • Systems for large-scale data analytics of textual and graph data
  • Large-scale optimization
  • Distributed computing (cloud, map-reduce, MPI)
  • Big Data Education and Learning
  • Big Data Information Banking
  • Novel Statistical techniques for Big Data
  • Big Data Issues and Applications
  • Big Data and Smart Computing Applications (Health Care, Medicine, Finance, Business, Law, Transportation, Telecommunication, Science, Engineering, etc.)

Who should Attend

• Research Scholars
• Professors
• Academicians