Researcher

Email that user will get. Mail will be sent on registered mail id. User will get paper title, authors, website link, and PDF link.
This is login page. User has to enter registered mail and password.
Here is the interests page where user can configure interest. User can get immediate mail if he clicks on get papers.
New users can register through register page.

Inspiration

The rising demand for researchers to keep up-to-date with the most recent research publications that are relevant to their interests served as an inspiration for our project. It was our goal to develop an automated system that makes finding research articles and getting suggestions for them easier, simplified, and more personalized.

What it does

Our project is a Web application that sends users suggestion emails based on their interests using the SMTP protocol. It downloads academic articles from well-known websites like IEEE, Science Direct, and Springer, and then emails each user a curated list of pertinent publications and PDF links. The system considers the user's preferences and offers them specialized recommendations. User may swiftly get papers and modify their interests whenever he wants.

How we built it

We used a number of technologies and parts to construct our system. Using Python and tools like BeautifulSoup and Selenium, we created a web scraping module to collect research articles from domains like IEEE, Science Direct, and Springer. With the aid of Flask, we created a user interface where users could enter their preferences and areas of interest. We connected an email distribution system utilizing the SMTP protocol, enabling us to send each customer a customized set of suggestion emails. Utilizing Firebase, we have saved user data in a database.

Challenges we ran into

Throughout the development process, we encountered a few challenges. One of the main hurdles was efficiently scraping research papers from various websites due to differences in their HTML structures. We had to adapt our scraping algorithms to handle different formats and ensure accurate extraction of relevant data. Additionally, implementing the email delivery system securely and efficiently was another challenge that required thorough testing and configuration.

Accomplishments that we're proud of

We're pleased to have developed a system that successfully automates the process of making research article recommendations based on user preferences. Our technology lowers the time and effort needed for researchers to find pertinent publications by offering personalized recommendations. A trustworthy email distribution system that guarantees users constantly receive their suggestions is another accomplishment we're proud of.

What we learned

During this project, we gained valuable knowledge and skills in web scraping techniques, email delivery protocols, and user interface development. We learned how to navigate and extract data from different websites with varying structures and improve the accuracy of the scraping process. Additionally, we deepened our understanding of SMTP and how to securely configure and utilize it for sending personalized emails.

What's next for Researcher

Our next efforts for Researcher include further optimising the recommendation system to increase the precision and relevancy of the publications users are recommended. To better understand customer preferences and progressively enhance the recommendations, we want to employ machine learning techniques. Additionally, we want to increase the system's capacity to get research papers from more reliable sources, broadening the selection of publications that can be recommended. In order to give researchers a more simple-to-use and seamless experience, we also intend to improve the user interface.