DMBD 2020 will feature plenary lectures given by worldwide renowned speakers, regular sessions with broad coverage, and some special sessions focused on some popular topics. Major topics to be addressed at the conference include, but are not limited to the following areas:

Topics of interest include, but are not limited to:

Data Mining
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

Algorithms
Association rules
Capability indices
Deviation and novelty detection
Conceptional learning
Inductive learning
Organisational Learning
Evolutional learning
Sampling methods
Similarity measures
Similarity learning
Statistical learning
Neural Net Based Learning
Feature Learning
Frequent pattern mining
Applications in all aspects of data mining

Big Data
Data models and architectures
Security, privacy, and trust
Data protection and integrity
Identity theft, data loss and leakage
Legal and ethicalissues
Data analytics and metrics
Data representation and structures
Data management and processing
Data capturing and acquisition
Tools and technologies QoS in big data

Applications
Social networks analysis
Data searching and mining
Visualisation of data
Personal data logging and quantified-self
Context-aware data
Data economics
Applications of datamining and big data
Methodologies and use cases
Usability issues
Storages and network requirements
Network models and protocols
Big data in cloud and IoT
Techniques for Big Data Processing