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Open Access Research Article

A landscape view of news recommendation systems based on MIND dataset

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* Corresponding author · click or hover a name for details

pp. 1705–1716Vol. 26Issue 6September 2023DOI: 10.47974/JDMSC-1617 Crossmark XML
Received:
05 Mar 2022
Accepted:
05 Apr 2022
Published Online:
01 Jun 2023
Article type:
Research Article
Language:
EN
Article no.:
JDMSC-1617
Pages:
1705–1716

Abstract

Nowadays, it’s a very important way for researchers and all people to find their desired meaning instead of searching for a specific topic. Recommendation systems are strategies to solve the problems of search, finding or reducing the time of interest content for users under complex information environments. R.S. can show us the related results that are close to what we desire. In this paper, we list rates of the most used techniques applied over MIND dataset and show the results and comparisons among these techniques, we have proposed our analysis on that dataset, which has been collected from Microsoft in 2019, and we proposed new techniques and explain the views of researchers in previous studies and the techniques in R.S. that depend on.

Keywords

Subject Classifications

Primary 93A30Secondary 49K15

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