Journal Recommendation System Using Content Based Filtering
Recommendation systems provide an approach to facilitate the user's desire. It is helpful in recommending the things from various domains. Researchers express their ideas and experience in an academic article for the research community. However, they have ample of options when they aspire to publish. At times, they end up with incorrect submission resulting in waste of time and effort of editor as well as himself. Journal selection has been a very tedious task for the novice authors. In this paper, Journal Recommendation System (JRS) is proposed, which will solve the problem of publication for many authors. Content based filtering method is used for this purpose. The dataset used is prepared by the authors and distance algorithm is used for recommendation.