#1. The Problem
For a long time, seeking the information from websites was based on keywords, but various recent studies have shown that the new way that is based on recommender systems is more effective and reliable in extracting useful knowledge from massive amounts of data.
In the field of academia, the exponential explosion in the number of scientific productions has
introduced more difficulty in filtering and accessing scientific information, making this field
very attractive and attracting the interest of several stakeholders. A large part of those are
trying to fix this problem using recommender system, for that reason we could see -according to
Google Scholar- that in the last 4 years (Since 2017) there were more than 15K scientific papers
for the query +scientific +“recommender system”.
#2. Our Solution
The project consists of developing a recommender system for scientific articles in order to facilitate the retrieval of the most relevant information for researchers in order to reduce the time wasted in the collection of articles.
#3. Objectives
The purpose of the system is to make scientific information more accessible to researchers in a reduced time and with optimal accuracy The system will be able to :
- Give the best results in terms of accuracy for scientific articles recommendation.
- Provide a user-friendly and intuitive environment for searching scientific information.
- Implement the conceptual and technical models and methods that yield the best software performance
- Build a robust enough system that properly meets the expectations of all stakeholders
- provide a system that is open to extension to any new recommendation method, which will subsequently allow for the testing of several solutions for generating scientific article recommendations.