Beschreibung
This book covers the types of Authorship Analysis techniques such as Authorship Verification, Authorship Attribution and Author Profiling. It covers the suitable stylistic features to increase the prediction accuracy of the demographic profiles such as gender, age and location. It covers the importance of feature selection algorithms to increase the accuracy of profiles prediction. It covers the importance of different term weight measures from various domains for better Author Profiling. In this book we explained one new term weight measure for strengthening the differentiating power of the feature thereby increasing the accuracies of profiles prediction in Author Profiling. This book also covers different types of approaches proposed by various researchers for Author Profiling with their merits, demerits, and limitations. This book also covers an alternative approach to address the draw backs of the existing approaches and to increase the efficiency of profiles prediction in Author Profiling.
Autorenporträt
T Raghunadha Reddy working as Associate Professor in Department of Information Technology, Vardhaman College of Engineering, Hyderabad. He completed his M.Tech from SIT, JNTUH, Hyderabad. He completed his Ph.D from JNTUH, Hyderabad. His areas of research interests are Data Mining, Machine Learning and Deep Learning.
Herstellerkennzeichnung:
OmniScriptum SRL
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E-Mail: info@omniscriptum.com
