Research collaboration connects distributed knowledge and competencies into new ideas and research institutes and has been the subject of many research projects. We argue that academic libraries, including libraries of universities and research institutes, hold a wealth of information regarding patrons' research interests hidden in their data bases. Mining these databases can provide better understanding of researchers' needs and interests. This paper has two main contributions. Firstly, it proposes a new methodology based on data mining techniques in library information systems to uncover patrons' research interests in order to facilitate research collaboration including interdisciplinary research. The proposed methodology, studies data mining techniques in a library information system as a case study and makes advantage of clustering algorithms to cluster researchers based on their library usage which is interpreted as their research interests. The second contribution of this paper is that, it presented a knowledge map as a visual representation of usage trends of an academic library to portray virtual interest groups based on item use information. The result of this study can support managers and decision makers for strategic decision making regarding future research directions and collaborations. The outcome of the case study confirms our hypotheses by revealing clusters of library users with similar research interests validated by their academic backgrounds.
Homayounvala, Elaheh, and Ammar Jalalimanesh. 2012. Promoting Research Collaboration Based on Data Mining Techniques in Library Information Systems. International Journal of Information Technology and Business Management ۸ (۱): ۷۳-۸۲.