Scientific Paper Recommendation: A Survey

TL;DR

This survey reviews the importance, algorithms, evaluation methods, and open challenges of scientific paper recommendation systems, highlighting their role in managing the exponential growth of scholarly literature.

Contribution

It provides a comprehensive overview of recommendation algorithms, evaluation techniques, and discusses open issues in scientific paper recommender systems.

Findings

Content-Based, Collaborative Filtering, Graph-Based, and Hybrid methods are key algorithms.

Evaluation methods include accuracy, diversity, and user satisfaction metrics.

Open issues include cold start, sparsity, scalability, privacy, and data standards.

Abstract

Globally, recommendation services have become important due to the fact that they support e-commerce applications and different research communities. Recommender systems have a large number of applications in many fields including economic, education, and scientific research. Different empirical studies have shown that recommender systems are more effective and reliable than keyword-based search engines for extracting useful knowledge from massive amounts of data. The problem of recommending similar scientific articles in scientific community is called scientific paper recommendation. Scientific paper recommendation aims to recommend new articles or classical articles that match researchers' interests. It has become an attractive area of study since the number of scholarly papers increases exponentially. In this survey, we first introduce the importance and advantages of paper recommender systems. Second, we review the recommendation algorithms and methods, such as Content-Based methods, Collaborative Filtering methods, Graph-Based methods and Hybrid methods. Then, we introduce the evaluation methods of different recommender systems. Finally, we summarize open issues in the paper recommender systems, including cold start, sparsity, scalability, privacy, serendipity and unified scholarly data standards. The purpose of this survey is to provide comprehensive reviews on scholarly paper recommendation.