Improvement of Translation Accuracy for the Word Sense Disambiguation System using Novel Classifier Approach

Ajith Abraham,Bineet Kumar Gupta,Satya Bhushan Verma,Archana Sachindeo Maurya,Mohammad Husain,Arshad Ali,Sami Alshmrany,Sanjay Gupta

#Bayes theorem #machine learning #machine translation #naïve bayes classification #supervised approach #unsupervised approach #and word sense disambiguation

Tracking Recurring Concepts from Evolving Data Streams using Ensemble Method

Yange Sun1,2, Zhihai Wang2, Jidong Yuan2, and Wei Zhang2 1School of Computer and Information Technology, Xinyang Normal University, China 2School of Computer and Information Technology, Beijing Jiaotong University, China

#Data streams # ensemble classification # change detection # recurring concept # Jensen-Shannon divergence

Enhanced Bagging (eBagging): A Novel Approach for Ensemble Learning

Goksu Tuysuzoglu1 and Derya Birant2 1Graduate School of Natural and Applied Sciences, Dokuz Eylul University, Turkey 2Department of Computer Engineering, Dokuz Eylul University, Turkey

#Bagging # boosting # classification algorithms # machine learning # random forest # supervised learning

Headnote Prediction Using Machine Learning Sarmad Mahar1, Sahar Zafar2, and Kamran Nishat1 1CoCIS, PAF-Karachi Institute of Economics and Technology, Pakistan 2Computer Science, Sindh Madressatul Islam University, Pakistan

Abstract: Headnotes are the precise explanation and summary of legal points in an issued judgment. Law journals hire

#Judgment summary # head-note prediction # machine learning # text summarization

Text Mining Approaches for Dependent Bug Report Assembly and Severity Prediction

Bancha Luaphol, Jantima Polpinij, Manasawee Kaenampornpan

#Bug report # dependent bug report assembly # bug severity prediction # threshold-based similarity analysis # cosine similarity # BM25 # term weighting # classification algorithm

MiNB: Minority Sensitive Na ve Bayesian Algorithm for Multi-Class Classification of

Unbalanced Data, Harikrishna Jethva

#Imbalanced data learning # weighted naïve bayesian # cost-sensitive learning # multi-class unbalanced data