Topic Areas

DMBD‘2016 will feature plenary lectures given by worldwide renowned speakers, regular sessions with broad coverage of data mining and data science, and some special sessions focused on the popular topics in data mining and big data. Major topics to be addressed at the DMBD'2016 conference include, but are not limited to the following areas:

Theory, algorithms and models of data mining
Machine learning for data mining
Statistical methods for data mining
Data mining systems
Mining text, semi-structured, spatio-temporal, streaming, graph, web, multimedia data
Data mining in personalization and recommendation
Case-Based Reasoning
Similarity-Based Reasoning
Clustering
Classification
Prediction
Association Rules
Experimentation strategy
Capability Indices
Deviation and Novelty Detection
Control Charts
Conceptional Learning
Inductive Learning
Organisational Learning
Evolutional Learning
Sampling Methods
Similarity Measures
Similarity learning
Statistical Learning
Neural Net Based Learning
Visualization
Feature Grouping, Discretization, Selection and Transformation
Feature Learning
Frequent Pattern Mining
Learning and Adaptive Control
Learning for Handwriting Recognition
Learning in Image Pre-Processing and Segmentation
Mining Financial Data
Mining Motion from Sequence
Subspace Methods
Support Vector Machines
Time Series and Sequential Pattern Mining
Desirabilities
Graph Mining
Agent Data Mining
Applications in Software Testing
Knowledge Management
Mining Social Media
Online Targeting & Controlling
Behavioral Targeting
Data Mining in Logistics
Data Mining in Energy Industry
Business Intelligence and Data Mining
Algorithm for Big Data
Legal Informatics


Data models and architectures
Security, privacy, and trust
Data protection and integrity
Identity theft, data loss and leakage
Legal and ethical issues
Data analytics and metrics
Data representation and structures
Data management and processing
Data capturing and acquisition
Tools and technologies
QoS in big data
Social networks analysis
Data searching and mining
Visualisation of data
Personal data logging and quantified-self
Context-aware data
Personalisation of data
Data economics
Applications of data mining and big data
Methodologies and use cases
Usability issues
Storages and network requirements
Network models and protocols
Big data in cloud and IoT

Foundational Models for Big Data
Algorithms and Programming Techniques for Big Data Processing
Big Data Analytics and Metrics
Representation Formats for Multimedia Big Data
Cloud Computing Techniques for Big Data
Big Data as a Service
Big Data in Mobile and Pervasive Computing
Big Data Persistence and Preservation
Big Data Quality and Provenance Control
Big Data Protection, Integrity and Privacy
Privacy Preserving Big Data Analytics
Big Data Encryption
Anomaly Detection in Very Large Scale Systems
Collaborative Threat Detection using Big Data Analytics
Algorithms and Systems for Big Data Search
Distributed, and Peer-to-peer Search
achine learning based on Big Data
Visualization Analytics for Big Data
Real-life Case Studies of Value Creation through Big Data Analytics
Big Data for Business Model Innovation
Big Data in Business Performance Management
SME-centric Big Data Analytics
Scientific Applications of Big Data
Challenges and opportunities in data mining and big data

Artificial Immune Systems
Autonomy-Oriented Computing
Artificial Neural Systems
Bayesian Learning
Biological Computing
Data Mining Cryptanalysis
DNA Computing
Evolutionary Programming
Evolutionary Algorithms
Image Understanding
Intelligent Systems
Knowledge Discovery|
Neural Networks
Probabilistic Reasoning
Reinforcement Learning
Supervised Learning

Fuzzy logic and design
Fuzzy pattern recognition
Uncertainty analysis
Game theory
Social Simulation
Fuzzy control
Fuzzy decision making/support
Rough sets
Fuzzy sets & Type-2 fuzzy logic
Approximate reasoning
Data analysis
Expert systems
Knowledge engineering

Applications of data mining in all domains
Big data applications