Rec4LRW : scientific paper recommender system for literature review and writing

• Main Authors: Foo, Schubert, Pang, Natalie, Sesagiri Raamkumar, Aravind
• Other Authors: Wee Kim Wee School of Communication and Information
• Format: Conference or Workshop Item
• Language: English
• Published: 2015
• Subjects: DRNTU::Engineering::Computer science and engineering::Information systems::Information storage and retrieval; DRNTU::Library and information science::Libraries::Information retrieval and analysis
• Online Access: https://hdl.handle.net/10356/107269; http://hdl.handle.net/10220/25515; http://dx.doi.org/10.3233/978-1-61499-503-6-106
• Institution: Nanyang Technological University

In this paper, we introduce Rec4LRW, a recommender system (RS) for assisting researchers in finding research papers for their literature review and writing purposes. This system focuses on three researcher tasks – (1) Building a reading list of research papers, (2) Finding similar papers based on a set of papers, and (3) Shortlisting papers from the final reading list for inclusion in manuscript based on article type. A set of intermediate criteria are proposed to capture the relations between a research paper and its bibliography. The recommendation techniques for the three tasks in Rec4LRW are specifically devised on top of the intermediate criteria. The Rec4LRW workflow along with the screen designs for the three tasks is provided in this paper. The recommendation techniques in the system will be evaluated with state-of-the-art approaches along with user-based evaluation in subsequent studies.