A Recommender System to Support the Scholarly Communication Process
Marko A. Rodriguez, David W. Allen, Joshua Shinavier, Gary, Ebersole

TL;DR
This paper introduces a context-sensitive recommender system leveraging Semantic Web standards to assist researchers with various scholarly communication tasks amid rapidly growing academic resources.
Contribution
It presents a novel recommender system tailored for scholarly communication, integrating Semantic Web technologies to address diverse researcher needs.
Findings
Supports multiple scholarly scenarios such as article discovery and collaborator search
Utilizes Semantic Web standards for improved recommendation accuracy
Enhances researcher decision-making in resource-rich environments
Abstract
The number of researchers, articles, journals, conferences, funding opportunities, and other such scholarly resources continues to grow every year and at an increasing rate. Many services have emerged to support scholars in navigating particular aspects of this resource-rich environment. Some commercial publishers provide recommender and alert services for the articles and journals in their digital libraries. Similarly, numerous noncommercial social bookmarking services have emerged for citation sharing. While these services do provide some support, they lack an understanding of the various problem-solving scenarios that researchers face daily. Example scenarios, to name a few, include when a scholar is in search of an article related to another article of interest, when a scholar is in search of a potential collaborator for a funding opportunity, when a scholar is in search of an…
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Taxonomy
TopicsRecommender Systems and Techniques · Semantic Web and Ontologies · Topic Modeling
