Difference between revisions of "PAKDD 2018"
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|State=Victoria | |State=Victoria | ||
|Country=Australia | |Country=Australia | ||
| + | |has general chair=Geoff Webb, Bao Ho | ||
| + | |has program chair=Dinh Phung, Vincent Tseng | ||
|Submitted papers=592 | |Submitted papers=592 | ||
|Accepted papers=164 | |Accepted papers=164 | ||
|has Proceedings Link=https://link.springer.com/book/10.1007%2F978-3-319-93034-3 | |has Proceedings Link=https://link.springer.com/book/10.1007%2F978-3-319-93034-3 | ||
}} | }} | ||
| + | Topics | ||
| + | |||
| + | As a premier international conference on knowledge discovery and data mining, PAKDD’18 welcomes all submissions on all aspects of knowledge discovery, data mining and machine learning. Suggestive topics of relevance for the conference include, but not limited to, the following: | ||
| + | |||
| + | |||
| + | * Theoretic foundations of KDD | ||
| + | * Deep learning theory and applications in KDD | ||
| + | * Novel models and algorithms | ||
| + | * Statistical methods and graphical models for data mining | ||
| + | * Anomaly detection and analytics | ||
| + | * Association analysis | ||
| + | * Clustering | ||
| + | * Classification | ||
| + | * Data pre-processing | ||
| + | * Feature extraction and selection | ||
| + | * Post-processing including quality assessment and validation | ||
| + | * Mining heterogeneous/multi-source data | ||
| + | * Mining sequential data | ||
| + | * Mining spatial and temporal data | ||
| + | * Mining unstructured and semi-structured data | ||
| + | * Mining graph and network data | ||
| + | * Mining social networks | ||
| + | * Mining high dimensional data | ||
| + | * Mining uncertain data | ||
| + | * Mining imbalanced data | ||
| + | * Mining dynamic/streaming data | ||
| + | * Mining behavioral data | ||
| + | * Mining multi-media data | ||
| + | * Mining scientific data | ||
| + | * Privacy preserving data mining | ||
| + | * Fraud and risk analysis | ||
| + | * Security and intrusion detection | ||
| + | * Visual data mining | ||
| + | * Interactive and online mining | ||
| + | * Ubiquitous knowledge discovery and agent-based data mining | ||
| + | * Integration of data warehousing, OLAP, and data mining | ||
| + | * Parallel, distributed, and cloud-based high-performance data mining | ||
| + | * Opinion mining and sentiment analysis | ||
| + | * Human, domain, organizational, and social factors in data mining | ||
| + | * Applications to healthcare, bioinformatics, computational chemistry, finance, eco-informatics, marketing, gaming, cyber-security, and industry-related problems | ||
Latest revision as of 20:17, 20 May 2020
| PAKDD 2018 | |
|---|---|
22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining
| |
| Event in series | PAKDD |
| Dates | 2018/06/03 (iCal) - 2018/06/06 |
| Homepage: | https://mamsap.it.deakin.edu.au/pakdd18/prada-research.net/pakdd18/index.html |
| Location | |
| Location: | Melbourne, Victoria, Australia |
Loading map... | |
| Papers: | Submitted 592 / Accepted 164 (27.7 %) |
| Committees | |
| General chairs: | Geoff Webb, Bao Ho |
| PC chairs: | Dinh Phung, Vincent Tseng |
| Table of Contents | |
Topics
As a premier international conference on knowledge discovery and data mining, PAKDD’18 welcomes all submissions on all aspects of knowledge discovery, data mining and machine learning. Suggestive topics of relevance for the conference include, but not limited to, the following:
- Theoretic foundations of KDD
- Deep learning theory and applications in KDD
- Novel models and algorithms
- Statistical methods and graphical models for data mining
- Anomaly detection and analytics
- Association analysis
- Clustering
- Classification
- Data pre-processing
- Feature extraction and selection
- Post-processing including quality assessment and validation
- Mining heterogeneous/multi-source data
- Mining sequential data
- Mining spatial and temporal data
- Mining unstructured and semi-structured data
- Mining graph and network data
- Mining social networks
- Mining high dimensional data
- Mining uncertain data
- Mining imbalanced data
- Mining dynamic/streaming data
- Mining behavioral data
- Mining multi-media data
- Mining scientific data
- Privacy preserving data mining
- Fraud and risk analysis
- Security and intrusion detection
- Visual data mining
- Interactive and online mining
- Ubiquitous knowledge discovery and agent-based data mining
- Integration of data warehousing, OLAP, and data mining
- Parallel, distributed, and cloud-based high-performance data mining
- Opinion mining and sentiment analysis
- Human, domain, organizational, and social factors in data mining
- Applications to healthcare, bioinformatics, computational chemistry, finance, eco-informatics, marketing, gaming, cyber-security, and industry-related problems
Facts about "PAKDD 2018"
| Acceptance rate | 27.7 + |
| Accepted papers | 164 + |
| Acronym | PAKDD 2018 + |
| End date | June 6, 2018 + |
| Event in series | PAKDD + |
| Event type | Conference + |
| Has coordinates | -37° 48' 51", 144° 57' 47"Latitude: -37.814244444444 Longitude: 144.96317222222 + |
| Has location city | Melbourne + |
| Has location country | Category:Australia + |
| Has location state | Victoria + |
| Homepage | https://mamsap.it.deakin.edu.au/pakdd18/prada-research.net/pakdd18/index.html + |
| IsA | Event + |
| Start date | June 3, 2018 + |
| Submitted papers | 592 + |
| Title | 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining + |
