Sells Sprint: Leveraging Machine-Learning Techniques for Ensuring Trust in Online Marketplaces
摘要
Essential services of buying and selling of goods, lost and found, finding volunteers or roommates might be a hectic task. We present this article on the Sells Sprint web application to meet this purpose. This is designed to assist people in carrying a two-way proceeding wherein one individual can post about selling of any goods, lost item, or jobs while the other person can make deals on this post, apply for the job, and so on. This is a kind of Craigslist that uses machine-learning techniques for automated screening of ads, job postings, and so on. The scalable and interpretable ML algorithm like Random Forest serves the purpose by detecting anomalies in various posts. Also, it helps people in connecting with local services like restaurants, salons, and other businesses and the fake ad classifier plugin helps build trust of the users by rapidly assessing the content and flagging the suspicious listings. Also, real time updates, searching, filtering, and greater intractability will be possible on Sells Sprint along with the promising authenticity of the content. The privacy of users is also taken into consideration by employing the anonymous email relay system wherein the sender’s details such as IP address and other personal information is anonymized.