Expert System for the Identification of Review Papers Using Ensemble Learning

Ghulam Mustafa
2021 Pakistan Social Sciences Review  
Creating an effective classifier in the presence of imbalanced data is a challenging task. The objective of this work was to apply machine learning technique to automatically identify review articles given the imbalance representation of publications types in publications. As a contribution in that direction; we develop a hybrid ensemble algorithm, called Balanced MultiBoost (BMB). The presented algorithm provides an efficient alternative to existing algorithms, by combines the strengths of
more » ... iboost ensemble with the sampling technique. In order to demonstrate the effectiveness of BMB, we compared its performance with five existing algorithms, based on established metrics, precision, recall, F1-measure and AUC-ROC. For the comparison, we used two customized datasets extracted from Medline citations database. These datasets contain 19,299 examples for 2005 and 19,200 examples for 2006 with imbalance ratio 1:6 and 1:7, respectively. The results show, BMB is a powerful ensemble solution for identifying minority examples in a text corpus.
doi:10.35484/pssr.2021(5-i)38 fatcat:f5michv2ibhx3gh6qwrz5prhve