A Metadata based Knowledge Discovery Methodology for Seeding Translational Research.
In this paper, we present a semantic, metadata based knowledge discovery methodology for identifying teams of researchers from diverse backgrounds who can collaborate on interdisciplinary research projects: projects in areas that have been identified as high-impact areas at The Ohio State University. This methodology involves the semantic annotation of keywords and the postulation of semantic metrics to improve the efficiency of the path exploration algorithm as well as to rank the results. Results indicate that our methodology can discover groups of experts from diverse areas who can collaborate on translational research projects.
Department of Biomedical Informatics, School of Medicine, The Ohio State University, Columbus, OH, USA.
Cartik R
CR
Kothari
Department of Biomedical Informatics, School of Medicine, The Ohio State University, Columbus, OH, USA.
Philip R O
PR
Payne
D057225:Data Mining / Q000379:methods; D016206:Databases, Bibliographic / Q000145:classification*; D058025:Interdisciplinary Studies; D051188:Knowledge Bases; D063369:Knowledge Discovery / Q000379:methods*; D000069550:Machine Learning; D000071253:Metadata / Q000145:classification*; D009323:Natural Language Processing; D010348:Patient Care Team / Q000458:organization & administration*; D010561:Personnel Staffing and Scheduling / Q000458:organization & administration*; D057170:Translational Research, Biomedical; D000078329:Workforce