Building Fexpert: System for searching experts in research university using K-MEANS algorithms

In a research university, it is difficult to search for an expert since there are many faculties and staff who might work in multidisciplinary areas. Researchers who work in the same project might not always be from the same department. It is the objective of this study to develop a prototype of an expert finding system (Fexpert) for a research university. Data were undertaken from three sources: (1) researcher´s personal profile, (2) graduate school profile and (3) research project profiles. The data were preprocessed and clustered according to each expert´s keywords using K-Means algorithm. The proposed system can be used to find experts according to the cluster of their research or keywords. The statistical analysis summarizes records of researchers by their works and unit areas. This study can be further applied for an expert finding system of a large organization which might be a part of Knowledge Management.