Query Fuel - In-house Query Solver

Abstract

The concept of peer learning dates back centuries, and with the increasing technology, it has become more accessible and easier for everyone to interact and learn from others. In such a situation, a common ground that brings everyone together plays a crucial role. Through sharing knowledge and experiences, people can build on the accomplishments of those who came before them and progress in various fields such as science, technology, medicine, and more. Various attempts have been made to make such a common platform, Quora and StackOverflow are two major players in this domain. Query fuel-an interactive community platform that aims to provide a similar solution with some features better than the existing solutions. The platform works on an organizational basis, where a registered user can post a query or any topic of discussion and let others participate. The organization and topic can vary from being a college to a support group where people feel safe discussing their discrete issues. Built on the MERN stack and having a custom ‘Query Searching Algorithm,’ the web application takes in the query as text input and passes through a search engine where we use the Probabilistic Ranking Algorithm and log-Linear Model Ranking Algorithm, which sets criterions for each query and rank them. This minimizes each query’s search time and enables the ‘Search as Type’ feature, which is not present in the existing systems. After thorough testing, we have come up with several metrics which prove that our solution is much more secure compared to the existing ones. Once we test the scalability with data in millions, we will be ready to ship this to the commercial market.