8Th PAKDD workshop on Bio-Inspired Data Mining (BDM'19)- April 14th- 17th, Macau, China

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Paper submission deadline:         Feb 25th, 2019
Author notification:               March 10, 2019
Camera-ready due:                  March 15, 2019 
Workshop day:                      April 14th, 2019
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To submit your paper use the following link: 
Website:https://bdm19.blogs.auckland.ac.nz 
Submission page:https://easychair.org/conferences/?conf=bdm19 	
  
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PAKDD 8TH workshop on “Biologically Inspired Techniques for Data Mining (BDM’19)”, 
is to be held in conjunction with 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining
 (PAKDD’19 ), April – 14th, 2019, Macau, China. PAKDD is one of the major conferences in knowledge
 discovery and data mining.
The workshop calls for high quality research papers outlining current research, literature surveys, 
theoretical and empirical studies, and other relevant work including but not limited to the following areas: 

1. Particle Swarm Optimization (PSO) 
PSO based clustering 
PSO based classification 
PSO based outlier detection 
PSO based feature selection 

2. Ant Colony Optimization (ACO) 
ACO based clustering 
ACO based classification 
ACO based outlier detection 
ACO based feature selection 
ACO based rules mining 
ACO based sequential patterns mining 

3. Artificial Neural Networks (ANN) 
ANN based pattern matching and discovery 
Classification rules discovery using ANN 
Forecasting and prediction analysis using ANN 

4. Genetic Algorithms (GAs) 
Clustering, classification and parameter tuning using GAs 
GAs based feature extraction and selection 
Learning Classifier Systems 

5. Artificial Immune System(AIS) 
AIS for intrusion detection 
AIS for data clustering 
AIS for decision support system 

6. Fuzzy Systems (FS) and biologically inspired techniques 
Fuzzy clustering 
Fuzzy classification 
Fuzzy Association rules discovery 

7. Bee Colony Optimization (BCO) 
BCO for pattern matching 
Clustering using BCO 
8. Evolutionary Neural Nets, Evolutionary SVMs, and Evolutionary Decision Trees 

9. Computational Intelligence in Recommender System


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To submit your paper use the following link: 
https://www.easychair.org/conferences/?conf=bdm19
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For more information please contact: 
Dr. Shafiq Alam, University of Auckland, New Zealand.
shafiq@cs.auckland.ac.nz