Master of Science (MS)
Thanh D. Tran
Natural language processing (NLP) is a technique by which computers can analyze, understand, and derive meaning from human language. Phrases in a body of natural text that represent names, such as those of persons, organizations or locations are referred to as named entities. Identifying and categorizing these named entities is still a challenging task, research on which, has been carried out for many years. In this project, we build a supervised learning based classifier which can perform named entity recognition and classification (NERC) on input text and implement it as part of a chatbot application. The implementation is then scaled out to handle very high-velocity concurrent inputs and deployed on two clusters of different sizes. We evaluate performance for various input loads and configurations and compare observations to determine an optimal environment.
Dabholkar, Shreeraj, "NAMED ENTITY RECOGNITION AND CLASSIFICATION FOR NATURAL LANGUAGE INPUTS AT SCALE" (2017). Master's Projects. 551.