Community Question-Answering Web Application

This project develops a web application that utilizes machine learning to enhance community question answering (CQA). To find related queries and score pertinent responses, the application employs Natural Language Processing (NLP) algorithms such as Word2Vec and Support Vector Machines (SVM). The algorithm continuously learns from user interactions and upvotes to improve its comprehension of the quality of answers and the relevancy of questions. In CQA forums, this model is a useful tool for decreasing duplicate material and enhancing user experience by offering scalable, automatic responses to frequently asked contextually relevant user questions.