Factoid Question and Answering System
Aditya SRM1, S.R Rajeswari2, Dinesh Reddy3, Varshini4
1S.R Rajeswari, Assistant Professor SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.
Aditya SRM Institute of Scienceand Technology, Chennai (Tamil Nadu), India.
Dinesh Reddy, SRM Institute of Scienceand Technology, Chennai (Tamil Nadu), India.
Varshini, SRM Institute of Scienceand Technology, Chennai (Tamil Nadu), India.
Manuscript received on 18 April 2019 | Revised Manuscript received on 25 April 2019 | Manuscript published on 30 April 2019 | PP: 60-61 | Volume-8 Issue-4, April 2019 | Retrieval Number: D6273048419/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: “The Natural Language processing (NLP)can be said as a form of artificial intelligence (AI) which is used to process the natural language data such as text, image, video, and audio. It acts as a tool for the computer to understand and analyse the real-time data in human language which the humans speak. Our system answers the factoid questions over texts, images using neural networks along with tensor flow framework. In order to justify the retrieved answer reasoning is also used. Reasoning is the process of analysing data in a logical way to make decisions. In question and answering system reasoning plays an important role for extracting the answers with better accuracy and precision”.
Keywords: NLP, AI, Chatbot, Fuzzy.
Scope of the Article: Fuzzy Logics