User Suggestions; Intelligent Discovery of Related Articles Based on User Visits

New Feature Introduction

Since the launch of Noormags, many users have viewed and downloaded its articles. Those who follow a specific topic in this database search for it in various ways.

How It Works

The co-occurrence statistics of Noormags' numerous users have been presented to them. Based on the viewing history of an article's readers, it has been determined which other articles have been viewed alongside that article.

If the statistical level of simultaneous views of two articles is high, it is highly likely that those two articles are related to each other.

Improving Results

With more user logs, better results will be achieved. Of course, this system has been created using user viewing logs and is prone to some margin of error.

Advantage Over Manual Methods

This method of enriching articles (providing related articles for a specific article) is practically impossible to do manually. Therefore, it is suggested that if you are seeking more and better answers for your research, benefit from the research results of other database users in this module.

Important Notes

• Articles that have been viewed by more users will yield better recommendations
• Since these related articles are provided through user logs, they will be updated from time to time
• The related articles for a given article in this system are not permanent; they are constantly changing