Rituparna Khaund
2020
Human Behavior Assessment using Ensemble Models
Abdullah Faiz Ur Rahman Khilji
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Rituparna Khaund
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Utkarsh Sinha
Proceedings of the 18th Annual Workshop of the Australasian Language Technology Association
Behavioral analysis is a pertinent step in today’s automated age. It is important to judge a statement on a variety of parameters before reaching a valid conclusion. In today’s world of technology and automation, Natural language processing tools have benefited from growing access to data in order to analyze the context and scenario. A better understanding of human behaviors would empower a range of automated tools to provide users a customized experience. For precise analysis, behavior understanding is important. We have experimented with various machine learning techniques, and have obtained a maximum private score of 0.1033 with a public score of 0.1733. The methods are described as part of the ALTA 2020 shared task. In this work, we have enlisted our results and the challenges faced to solve the problem of the human behavior assessment.