PAKDD 2020

The document "PAKDD 2020" was published on "2022-10-19T14:18:50" on the website "ConfIDent" under the URL https://confident-conference.org/index.php/Event:PAKDD 2020.

The document "PAKDD 2020" describes an event in the sense of a conference.

The document "PAKDD 2020" contains information about the event "PAKDD 2020" with start date "2020/05/11" and end date "2020/05/14".

The event "PAKDD 2020" is part of the event series identified by [[Event Series:PAKDD]]

Deadlines

Metrics

Submitted Papers

628

Accepted Papers

135

Venue

Singapore

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Due to the unexpected COVID-19 epidemic, we made all the conference sessions accessible online to participants around the world.

Topics

• Anomaly detection and analytics
• Association analysis
• Classification
• Clustering
• Data pre-processing
• Deep learning theory and applications in KDD
• Explainable machine learning
• Factor and tensor analysis
• Feature extraction and selection
• Fraud and risk analysis
• Human, domain, organizational, and social factors in data mining
• Integration of data warehousing, OLAP, and data mining
• Interactive and online mining
• Mining behavioral data
• Mining dynamic/streaming data
• Mining graph and network data
• Mining heterogeneous/multi-source data
• Mining high dimensional data
• Mining imbalanced data
• Mining multi-media data
• Mining scientific data
• Mining sequential data
• Mining social networks
• Mining spatial and temporal data
• Mining uncertain data
• Mining unstructured and semi-structured data
• Novel models and algorithms
• Opinion mining and sentiment analysis
• Parallel, distributed, and cloud-based high-performance data mining
• Post-processing including quality assessment and validation
• Privacy preserving data mining
• Recommender systems
• Representation learning and embedding
• Security and intrusion detection
• Statistical methods and graphical models for data mining
• Supervised learning
• Theoretic foundations of KDD
• Ubiquitous knowledge discovery and agent-based data mining
• Unsupervised learning
• Visual data mining
• Applications to healthcare, bioinformatics, computational chemistry, finance, eco-informatics, marketing, gaming, cyber-security, and industry-related problems