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A Context-Aware Vocabulary Management and Reading Assistance System using Machine Learning and Natural Language Processing

Authors

Zhanhao Cao1 and Yu Sun2, 1USA, 2California State Polytechnic University, USA

Abstract

Through the increase in the popularity of online reading, many people rely on online dictionaries to further understand the text [1]. However, looking up a word manually is a great inconvenience as well as a form of distraction [2]. This paper develops a chrome extension to automatically detect the difficult words for each user, and provide the words’ associated definition with a mouse hover. The chrome extension can be customized by adding and removing personal difficult words and personal easy words [3]. Also, the chrome extension offers a deeper level of analytic, including the system analyzing part of speech of the world, to further understand the definition of a selected word or sentence. The chrome extension is applied to a school/work setting in order to improve the working efficiency by providing a simple model to analyze the word definition; it is also useful for casual reading, especially to those that aren’t fluent in English. Following the strict SDLC model, the end of the testing stage reflects that most of the users gave positive feedback to the chrome extension with most of the comments centered around convenience and accuracy [4]. Through alpha testing and a small sample of beta testing, the Chrome extension presents productivity improvement on difficult texts.

Keywords

Chrome Extension, NLP, Cloud Computing.

Full Text  Volume 12, Number 10