Difference between revisions of "PAKDD 2020"
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|Title=24th Pacific-Asia Conference on Knowledge Discovery and Data Mining | |Title=24th Pacific-Asia Conference on Knowledge Discovery and Data Mining | ||
|Series=PAKDD | |Series=PAKDD | ||
− | | | + | |Event type=Conference |
|Start date=2020/05/11 | |Start date=2020/05/11 | ||
|End date=2020/05/14 | |End date=2020/05/14 |
Latest revision as of 11:13, 8 March 2021
PAKDD 2020 | |
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24th Pacific-Asia Conference on Knowledge Discovery and Data Mining
| |
Event in series | PAKDD |
Dates | 2020/05/11 (iCal) - 2020/05/14 |
Homepage: | https://pakdd2020.org/ |
Location | |
Location: | Singapore, Republic of Singapore |
Papers: | Submitted 628 / Accepted 135 (21.5 %) |
Committees | |
General chairs: | Ee-Peng Lim, See-Kiong Ng |
PC chairs: | Hady Lauw, Raymond Wong, Alexandros Ntoulas |
Table of Contents | |
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