Neural Intent Recognition for Question-Answering System

Indulkar, Ajinkya Pradeep and Varadharajan, Srivatsan and Nayak, Krishnamurthy (2018) Neural Intent Recognition for Question-Answering System. International journal of innovative research in technology, 5 (3). pp. 54-65. ISSN 2349-6002

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Conversational Agents, commonly known as Chatbots, are a successful result of the collaboration of Natural Language Processing (NLP) and Deep Learning. Major Technology Giants like Google, Amazon, Microsoft, etc. are heavily invested in developing a sophisticated conversational agent which can pass the Turing Test. There are various methodologies which can be used to develop the various components of such an agent from scratch. This paper uses SQuAD, an open Question-Answering dataset, for developing an Intent Recognition System for any Question-Answering system. Inspired by Author-Topic Modelling, a Title-Topic Modelling technique is used in combination with various Deep Learning models to train the Intent Recognition System, achieving an accuracy of 88.36%.

Item Type: Article
Uncontrolled Keywords: Conversational Agents, Deep Learning, Intent Recognition, Natural Language Processing, Question-Answering System, Title-Topic Modelling
Subjects: Engineering > MIT Manipal > Electronics and Communication
Depositing User: MIT Library
Date Deposited: 30 Jan 2019 10:45
Last Modified: 30 Jan 2019 10:45

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