Abstract
Quora is a place to gain and share knowledge. It's a platform to ask questions and connect with people who contribute unique insights and quality answers. In September 2018, Quora reportedly hit 300 million monthly users. With over 300 million people visiting Quora every month, it’s no surprise that many people ask duplicated questions, that is, questions that have same intent. Multiple questions with the same intent can cause seekers to spend more time finding the best answer to their question and make writers feel they need to answer multiple versions of the same question. Quora values canonical questions because they provide a better experience to active seekers and writers, and offer more value to both of these groups in the long term. The main aim of this work is to apply various natural language processing (NLP) concepts for feature extraction from the given dataset and apply machine learning model XG Boost to predict the similarity.
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Chunamari, A., Yashas, M., Basu, A., Anirudh, D.K., Soumya, C.S. (2022). Quora Question Pairs Using XG Boost. In: Shetty, N.R., Patnaik, L.M., Nagaraj, H.C., Hamsavath, P.N., Nalini, N. (eds) Emerging Research in Computing, Information, Communication and Applications. Lecture Notes in Electrical Engineering, vol 790. Springer, Singapore. https://doi.org/10.1007/978-981-16-1342-5_55
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DOI: https://doi.org/10.1007/978-981-16-1342-5_55
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