Recommender Systems for Science: A basic Taxonomy

<p>This dataset is accompanying the &quot;<strong>Recommender system for science: A basic taxonomy</strong>&quot; paper published at IRCDL 2022 conference.&nbsp;</p> <p>This study had a Systematic Mapping Approach on the Recommender system for science. In particular, the study aims at responding to four questions on recommender systems in science cases: users and their interests representation, item typologies and their representation, recommendation algorithms, and evaluation, and then providing a taxonomy.&nbsp;</p> <p>This dataset contains&nbsp;<strong>209 papers&nbsp;</strong>of interest that have been published between 2015 and 2022.</p> <p>The dataset has <strong>11</strong> columns which organised as follows:&nbsp;</p> <p>Column&nbsp;<strong>Title:&nbsp;</strong>This column contains the title of the papers.</p> <p>Column&nbsp;<strong>DOI:&nbsp;</strong>This column contains the DOI of the papers.</p> <p>Column&nbsp;<strong>Publication_year</strong>: This column contains the year that the paper is published.</p> <p>Column&nbsp;<strong>DB:&nbsp;</strong>This column contains the repository that the paper is retrieved.</p> <p>Column&nbsp;<strong>Keywords</strong>: This column contains the keywords provided for the paper.</p> <p>Column&nbsp;<strong>Content_type:&nbsp;</strong>This column contains the paper type which can be:&nbsp;<strong>Article,</strong>&nbsp;<strong>Conference</strong>&nbsp;or&nbsp;<strong>Review.</strong></p> <p>Column&nbsp;<strong>Citing_paper_count:&nbsp;</strong>This column contains the citation number of the paper.</p> <p>Column&nbsp;<strong>Recommended_artefact:&nbsp;</strong>This column contains the scientific product that is recommended to users which can be <strong>paper</strong>, <strong>workflow</strong>, <strong>collaborator</strong>, <strong>dataset</strong> or <strong>others</strong>.</p> <p>Column&nbsp;<strong>User_type:&nbsp;</strong>This column contains the type of user who receives the recommendation, which can be&nbsp;an<strong> Individual </strong>user&nbsp;or&nbsp;a<strong> Group</strong>&nbsp;of users.</p> <p>Column&nbsp;<strong>Algorithm</strong><strong>:&nbsp;</strong>This column contains the recommendation algorithm that the paper proposed, which can be:&nbsp;<strong>HB&nbsp;</strong>(Hybrid-based),&nbsp;<strong>CB</strong>&nbsp;(Content-based),&nbsp;<strong>CFB</strong>&nbsp;(Collaborative-filtering-based), or&nbsp;<strong>GB</strong>&nbsp;(Graph-based).</p> <p>Column&nbsp;<strong>Evaluation_method</strong><strong>:&nbsp;</strong>This column contains the method of the algorithm evaluation which can be&nbsp;<strong>OFFLINE</strong>,&nbsp;<strong>ONLINE, BOTH,&nbsp;</strong>or<strong>&nbsp;NO_EVALUATION.</strong></p>