A systematic review of similar Questions Retrieval Approaches
Abstract
A renowned online community known as Quora enables members to post queries, receive insightful responses, and share knowledge. The capacity of Quora to find related questions based on a user's search is a distinctive feature that makes it simple for users to access pertinent information and add it to the platform's knowledge base. The retrieval of comparable questions from Quora is the topic of this paper. We assess various systems that classify related queries and quickly deliver pertinent responses to information searchers. Our assessment of machine learning and natural language processing methods focuses on how well these methods work when obtaining queries from the large Quora question database that serves related objectives. Our thorough research paper provides a summary of the literature on comparable question retrieval in Quora while highlighting the benefits and drawbacks of various approaches. Our evaluation identifies prospective topics for more research and development and acts as a guide for future scholars interested in this field. By enhancing similar question retrieval on Quora, we hope to encourage knowledge-sharing and community development on this important platform. Users can find the most pertinent responses to their inquiries on Quora by using the study's findings.
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