Difference between revisions of "PAKDD 2019"

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(Created page with "{{Event |Acronym=PAKDD 2019 |Title=23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining |Series=PAKDD |Type=Conference |City=Macau |Country=China }} Topics...")
 
 
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|Series=PAKDD
 
|Series=PAKDD
 
|Type=Conference
 
|Type=Conference
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|Start date=2019/04/14
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|End date=2019/04/17
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|Homepage=https://pakdd2019.medmeeting.org/Content/100312
 
|City=Macau
 
|City=Macau
 
|Country=China
 
|Country=China
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|has general chair=Qiang Yang, Zhi-Hua Zhou
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|has program chair=Zhiguo Gong, Min-Ling Zhang
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|has workshop chair=Hady W. Lauw, Leong Hou U
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|Submitted papers=628
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|Accepted papers=135
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|has Proceedings Link=https://link.springer.com/book/10.1007%2F978-3-030-16142-2
 
}}
 
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Topics  
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Topics  
  
 
PAKDD 2019 welcomes high-quality, original and previously unpublished submissions in the theory, practice, and applications on all aspects of knowledge discovery and data mining. Topics of relevance for the conference include, but not limited to, the following:  
 
PAKDD 2019 welcomes high-quality, original and previously unpublished submissions in the theory, practice, and applications on all aspects of knowledge discovery and data mining. Topics of relevance for the conference include, but not limited to, the following:  

Latest revision as of 20:28, 20 May 2020

PAKDD 2019
23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining
Event in series PAKDD
Dates 2019/04/14 (iCal) - 2019/04/17
Homepage: https://pakdd2019.medmeeting.org/Content/100312
Location
Location: Macau, China
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Papers: Submitted 628 / Accepted 135 (21.5 %)
Committees
General chairs: Qiang Yang, Zhi-Hua Zhou
PC chairs: Zhiguo Gong, Min-Ling Zhang
Workshop chairs: Hady W. Lauw, Leong Hou U
Table of Contents


Event


Topics

PAKDD 2019 welcomes high-quality, original and previously unpublished submissions in the theory, practice, and applications on all aspects of knowledge discovery and data mining. 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