The problem PaperPilot.AI solves

PaperPilot aims to solve the problem of scholars and researchers struggling to discover relevant research papers amidst the abundance of academic papers available online. With the vast collection of high-quality academic papers across various domains, it can be overwhelming for individuals to find papers that match their research interests. This problem can lead to wasted time and effort in searching for relevant papers, which can delay or hinder research progress.

To address this problem, PaperPilot leverages artificial intelligence and advanced recommendation algorithms to cluster research papers based on their content and similarity. This approach ensures accurate and tailored recommendations that cater to each user's specific needs, making the process of discovering relevant research papers more efficient and effective.

Furthermore, PaperPilot delivers periodic research paper recommendations directly to users' email inboxes, eliminating the need for users to manually search for new papers regularly. This feature saves users time and effort and ensures that they stay up-to-date with the latest research in their field.

In summary, PaperPilot solves the problem of scholars and researchers struggling to discover relevant research papers by providing personalized recommendations based on their research interests. This approach saves users time and effort, ensures that they stay up-to-date with the latest research, and ultimately helps to accelerate research progress.

Challenges we ran into

One of the biggest challenges we faced was scraping the research papers from the IEEE website. We had to ensure that the dataset was extensive and high-quality, which required significant effort and time. Additionally, integrating AWS email services and ensuring that the recommendations were delivered accurately and timely was another challenge we faced.