| Popis: |
One of the main steps in publication of a paper is finding a related journal for the work of the researchers. In the recent years, there have been an increase in scientific papers publications. This situation leads the introduction of journal recommender systems by leading academic publishers. Without using a journal recommender system, this step would be a very time consuming task. This study reviewed similar studies in the literature. Current study is the first version of journal recommender system for TRDIZIN index which has an increasing amount of articles. A dataset is created by collecting titles, keywords, and abstracts of papers from dergipark web page. Using the collected dataset, a target journal from TRDIZIN is suggested according to title, abstract and keyword of the given article. For the first version of the journal recommender system, cosine similarity is used. The results of the suggested algorithm are evaluated by using performance criteria as the nearest 5 and 10 journals' accuracy. |
