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Algorithms for effective team building

Date Issued
2013
Author(s)
Ivanovska, Sashka
Abstract
Effective team building is an important issue of human
resource management (HRM). In order to keep up with
technological improvements and changes, selecting the right
person for the right job position is very important. This paper
describes a research and development methodology for
establishing a more sophisticated approach for composing
effective teams.
Data mining (DM) techniques and algorithms, like decision
trees, Bayesian networks and fuzzy logic, were utilized to
build a model to predict the best possible person for a specific
job. We have applied K-means and fuzzy C-means clustering
and decision tree classification algorithms. Pruned and
unpruned trees were contributed using ID3, C4.5 and CART
algorithms. By using these techniques, the patterns of
employee performance were generated. To validate the
generated model, several experiments were conducted using
data collected from IT companies. After evaluation, the most
appropriate algorithms are recommended to be used in the
process of effective team building.
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10CiiT-17.pdf

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(MD5):9f94d6d33e821cbe2f9ddc95ccd6a213

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