Biologically Inspired Techniques for Data Mining (BDM 2017)

May 23-26,2017

Jeju, South Korea.

Call For Papers

The workshop highlights a relatively new but fast growing area of data mining which is based on optimization techniques from biological behaviour of animals, insects, cultures, social behaviors and biological evolution. Techniques based on these models have been studied substantially, well optimized and tuned for different application areas in the previous decade. Knowledge Discovery and Data mining has been observed as one of the fastest growing application area of these nature inspired techniques.

Topics of Interest

Particle Swarm Optimization (PSO)

PSO based clustering

PSO based classification

PSO based outlier detection

PSO based feature selection

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

Artificial Neural Networks (ANN)

ANN based pattern matching and discovery

Classification rules discovery using ANN

Forecasting and prediction analysis using ANN

Genetic Algorithms (GAs)

Clustering, classification and parameter tuning using GAs

GAs based feature extraction and selection

Learning Classifier Systems

Artificial Immune System(AIS)

AIS for intrusion detection

AIS for data clustering

AIS for decision support system

Fuzzy Systems (FS) and biologically inspired techniques

Fuzzy clustering

Fuzzy classification

Fuzzy Association rules discovery

Bee Colony Optimization (BCO)

BCO for pattern matching

Clustering using BCO

Evolutionary Neural Nets, Evolutionary SVMs, and Evolutionary Decision Trees

Important Dates

Submission deadline: December 23, 2016.

Notification Due:January 22, 2017.

Final Version Due: February 8, 2017.

User Name : Anika
Posted 24-11-2016 on 10:55:04 AEDT

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