Text Analyzer for Competitive Examination

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Author(s)

Ashwini Dalvi 1 Irfan Siddavatam 1 Sagar Ailani 1 Smith Dedhia 1 Shyamal Makwana 1

1. Department of Information Technology, K.J.Somaiya College of Engineering, Mumbai-400077,India

* Corresponding author.

DOI: https://doi.org/10.5815/ijeme.2019.06.03

Received: 6 Jul. 2019 / Revised: 2 Aug. 2019 / Accepted: 30 Aug. 2019 / Published: 8 Nov. 2019

Index Terms

GRE, TOEFL, NLP, text processing, topic modeling

Abstract

Competitive examination provide a platform to the user for gauging their verbal and literature skills. The tools available currently only provide some simple feature regarding text processing such as spelling correction and providing different synonyms of the selected words. A complete assessment is not done for the user’s abilities and relevant details related to the context are not taken entirely into consideration. The following paper proposes a way to implement Natural Language Processing on text to provide feedback to the user for their competitive examinations. The assessment of the text will be done according to the parameter such as grammar, vocabulary; relevance to the context.
Some applications for web and mobile platform are available to offer assessment of English language essay but limited academic research available to validate research work in this domain. This work is effort to address requirement of text analyzer for English language evaluation methods incorporating natural language processing.

Cite This Paper

Ashwini Dalvi, Irfan Siddavatam, Sagar Ailani, Smith Dedhia, Shyamal Makwana," Text Analyzer for Competitive Examination", International Journal of Education and Management Engineering(IJEME), Vol.9, No.5, pp.25-34, 2019. DOI: 10.5815/ijeme.2019.06.03

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