Information Processing in Research Paper Recommender System Classes

Author:

Maake Benard M.1,Ojo Sunday O.1,Zuva Tranos2

Affiliation:

1. Tshwane University of Technology, South Africa

2. Vaal University of Technology, South Africa

Abstract

Research-related publications and articles have flooded the internet, and researchers are in the quest of getting better tools and technologies to improve the recommendation of relevant research papers. Ever since the introduction of research paper recommender systems, more than 400 research paper recommendation related articles have been so far published. These articles describe the numerous tools, methodologies, and technologies used in recommending research papers, further highlighting issues that need the attention of the research community. Few operational research paper recommender systems have been developed though. The main objective of this review paper is to summaries the state-of-the-art research paper recommender systems classification categories. Findings and concepts on data access and manipulations in the field of research paper recommendation will be highlighted, summarized, and disseminated. This chapter will be centered on reviewing articles in the field of research paper recommender systems published from the early 1990s until 2017.

Publisher

IGI Global

Reference108 articles.

1. Abel, F., Celik, I., Hauff, C., Hollink, L., & Houben, G.-J. (2011). U-sem: Semantic enrichment, user modeling, and mining of usage data on the social web. arXiv preprint arXiv:1104.0126

2. Science Concierge: A Fast Content-Based Recommendation System for Scientific Publications

3. Alotaibi, S., & Vassileva, J. (2015). Multi-dimensional Ratings for Research Paper Recommender Systems: A Qualitative Study. Paper presented at the International Symposium on Web AlGorithms, Deauville, France.

4. Alzoghbi, A., Ayala, V. A. A., Fischer, P. M., & Lausen, G. (2016). Learning-to-Rank in Research Paper CBF recommendation: Leveraging Irrelevant Papers. Paper presented at the CBRecSys@ RecSys, Boston, MA.

5. Information Extraction as Link Prediction: Using Curated Citation Networks to Improve Gene Detection

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