Serendipitous recommendation for scholarly papers considering relations among researchers

Serendipity occurs when one finds an interesting discovery while searching for something else. In digital libraries, recommendation engines are particularly well-suited for serendipitous recommendations as such processes work without needing queries. Junior researchers can use such scholarly recommendation systems to broaden their horizon and learn new areas, while senior researchers can discover interdisciplinary frontiers to apply integrative research. We adapt a state-of-the-art scholarly paper recommendation system’s user profile construction to make use of information drawn from 1) dissimilar users and 2) co-authors to specifically target serendipitous recommendation. Categories and Subject Descriptors H.3.3 [Information Search and Retrieval]: Information filtering, Search process; H.3.7 [Digital Libraries]: Systems issues General Terms Algorithms, Experimentation, Human factors, Performance Keywords Recommendation, Serendipity, User modeling

• Type: Journal
• Year: 2011
• Where: JCDL
• Authors: Kazunari Sugiyama, Min-Yen Kan
• Keywords: Digital Libraries, Education, JCDL 2011, Recommendation Engines, Recommendation Systems