Journal recommendation system

This is a collaborative project.

We intend to provide a system which recommends the most relevant journals to researchers.

• Motivation:
  • Help researchers easier to find the journals based on their paper about Covid-19 or they may have a better shot at publishing in these recommended journals.
  • Help researchers to find papers for reference more efficiently.

We use a text CNN model which has three different filters to find top 5 most relevant journals.

Additionally, we set up an interface by React.js and Flask for people to access.

The website is hosted on Google Cloud Platform (GCP). It is divided into three parts:

1. Dashboard: We can see the number of cumulative cases of COVID-19 and reported cases from it.

dash.mov

2. Result: Researchers can enter their abstracts as query and find the journals.

3. Team: Introduce our team members.

• Responsibilities:

  • Built a website using React.js and Flask
  • Deployed a text CNN model recommending journals for researchers on the website
  • Gained experience in setting up a website on Google App Engine (GAE)
  • Collaborated with team members from different disciplines

Technologies: Python, GCP, React, Flask