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