Topic Areas
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 |
Algorithms |
Big Data |
Applications |
- 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
- 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
|
- 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
|
- 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
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