2023International Journal of Membrane Science and TechnologyOpen access

Hybrid-based Research Article Recommender System

Su-Anne Teh, Su-Cheng Haw, Heru Agus Santoso

Open full text 3 citations

Abstract

A recommender system, which might assist in providing clients with new information and a better experience, is becoming increasingly popular in this era of modernization. Recommender systems are often used by various platforms to provide new products to consumers, which may also help in improving product sales. Additionally, the recommender system is essential in academic domains. It is common for users to take a while to find and access the materials they need. The recommender system is now available, which could reduce the time spent looking for materials and improve student achievement. Therefore, it is crucial to explore more on the theory and implementation of the recommender system. This paper aims to study a few types of recommender system techniques and implement it in the research article recommender system. Additionally, related research on each of the three recommender systems will be reviewed, along with a description of the related study, the dataset used, and the evaluation method.

About this research paper

What this paper is about

A recommender system, which might assist in providing clients with new information and a better experience, is becoming increasingly popular in this era of modernization. Recommender systems are often used by various platforms to provide new products to consumers, which may also help in improving product sales. Additionally, the recommender system is essential in academic domains. It is common for users to take a while to find and access the materials they need. The recommender system is now available, which could reduce the time spent looking for materials and improve student achievement. Therefore, it is crucial to explore more on the theory and implementation of the recommender system. This paper aims to study a few types of recommender system techniques and implement it in the research article recommender system. Additionally, related research on each of the three recommender systems will be reviewed, along with a description of the related study, the dataset used, and the evaluation method.

Why it matters

OpenAlex reports 3 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

A recommender system, which might assist in providing clients with new information and a better experience, is becoming increasingly popular in this era of modernization. Recommender systems are often used by various platforms to provide new products to consumers, which may also help in improving product sales. Additionally, the recommender system is essential in academic domains. It is common for users to take a while to find and access the materials they need. The recommender system is now available, which could reduce the time spent looking for materials and improve student achievement. Therefore, it is crucial to explore more on the theory and implementation of the recommender system. This paper aims to study a few types of recommender system techniques and implement it in the research article recommender system. Additionally, related research on each of the three recommender systems will be reviewed, along with a description of the related study, the dataset used, and the evaluation method.

Key concepts: Recommender system, Computer science, Product (mathematics), World Wide Web, Geometry, Mathematics

Related papers

Back to paper searchBrowse research topicsOriginal source
Hybrid-based Research Article Recommender System — Research Paper | ScholarLens