Research Article
Design and Development of Rule-based open-domain Question-Answering System on SQuAD v2.0 Dataset
@INPROCEEDINGS{10.4108/eai.24-3-2022.2318995, author={Pragya Katyayan and Nisheeth Joshi}, title={Design and Development of Rule-based open-domain Question-Answering System on SQuAD v2.0 Dataset}, proceedings={Proceedings of the 3rd International Conference on ICT for Digital, Smart, and Sustainable Development, ICIDSSD 2022, 24-25 March 2022, New Delhi, India}, publisher={EAI}, proceedings_a={ICIDSSD}, year={2023}, month={5}, keywords={question answering natural language processing information retrieval artificial intelligence}, doi={10.4108/eai.24-3-2022.2318995} }- Pragya Katyayan
Nisheeth Joshi
Year: 2023
Design and Development of Rule-based open-domain Question-Answering System on SQuAD v2.0 Dataset
ICIDSSD
EAI
DOI: 10.4108/eai.24-3-2022.2318995
Abstract
Human mind is the palace of curious questions that seek answers. Computational resolution of this challenge is possible through Natural Language Processing techniques. Statistical techniques like machine learning and deep learning require a lot of data to train and despite that they fail to tap into the nuances of language. Such systems usually perform best on close-domain datasets. We have proposed development of a rule-based open-domain question-answering system which is capable of answering questions of any domain from a corresponding context passage. We have used 1000 questions from SQuAD 2.0 dataset for testing the developed system and it gives satisfactory results. In this paper, we have described the structure of the developed system and have analyzed the performance.