Article Recommender System Launched on Noormags
New Service Introduction
According to Noorsoft, Engineer Bashari Movahed, an intelligent processing developer at the Noor Computer Research Center for Islamic Sciences (Noor), announced the launch of the valuable Article Recommender System on the Noor Specialized Journals Database (Noormags) in an interview.
He added: Today, due to the ever-increasing volume of information on the internet, there is a need for systems that can recommend the most relevant content to users. Systems that perform this task are called Recommender Systems.
Types of Recommender Systems
Engineer Mohammad Hassan Bashari Movahed explained this system:
"Recommender systems use specific algorithms and methods to identify the most relevant content and suggest those closest to the user's taste. They typically present recommendations in one of three forms: Collaborative Filtering, Content-Based, or Personalized approaches."
Three Models Implemented in Noormags
The intelligent processing developer at Noor Center stated that all three models of recommender systems have been implemented in Noormags:
1. Collaborative Filtering
This model is built based on the user's past behavior and similar decisions made by other users. Using the created model, items that may be of interest to the user are introduced. In this mode, alongside each article, a list of articles is presented based on the behavior of other users.
2. Personalized Recommender System
Regarding another model of the article recommender system in Noormags, he said:
"The personalized recommender system, which is another model for providing article recommendations, has also been implemented in Noormags. It infers user preferences based on their tendencies toward specific articles and suggests a list of articles to the user."
Instant Update Feature
Referring to the accuracy and speed of the recommender system implemented in Noormags, he added:
"One of the important features of this system, achieved through the efforts of the technical team at Noor Center, is the instant and continuous updating of the suggested article list for users. Given the vast volume of user logs in Noormags, this feature is of great importance."
Real-time Update Capability
Engineer Bashari Movahed added:
"With the implementation of this recommender system model in Noormags, as soon as a user accesses a new article, the list of suggested articles is updated, and the user is notified of the update."
Related Articles Feature (Lexical Similarity)
He also mentioned another feature called Related Articles in Noormags:
"This feature, which involved extensive programming work, uses artificial intelligence to examine lexical similarity between articles. It connects articles that share such similarities and presents this list to users beneath each article. Consequently, researchers can easily view and use articles that are lexically related to their desired content."
Importance and Application
At the end, Engineer Bashari Movahed emphasized the importance of the recommender system in Noormags:
"Given the vast number of articles in this database, the recommender system can serve as a complement to search algorithms and help researchers find articles they might not have been able to discover through search alone. Recommender systems, using their specific algorithms, interestingly index new data, which can greatly assist researchers in completing their research process."