Abstract
In recent years, there has been a rapid increase in the number of research papers being published, leading to what many feel is an overload of information. This makes it difficult for researchers to choose the right journal for their work. To help with this, journal recommender systems have been suggested as useful tools to help researchers find the most appropriate journals for their research. With so many journals, publishers, and recommender systems to choose from, deciding on the best one can be complicated. This decision depends on several factors, including the publisher, the scientific database, and the specific needs and preferences of the user. In this paper, we offer a detailed comparison of popular journal recommender systems, both theoretically and through experiments, to see how effective they are at making recommendations. We focus on how relevant and helpful these recommendations are. We also provide advice for researchers on how to make the most of these recommender systems to aid in their publishing process.
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