Expertise Retrieval: Foundations, Methods and Models
Objective: Expertise Retrieval is defined as finding experts in different subject areas as well as identifying people expertise area(s). For almost two decades, ER within knowledge-based environments has attracted attention of large and medium organizations. It has given rise to a strong community o...
| Main Authors: | , , |
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| Format: | Article |
| Language: | fas |
| Published: |
Iranian Research Institute for Information and Technology
2016-06-01
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| Series: | Iranian Journal of Information Processing & Management |
| Subjects: | |
| Online Access: | http://jipm.irandoc.ac.ir/browse.php?a_code=A-10-3193-1&slc_lang=en&sid=1 |
| Summary: | Objective: Expertise Retrieval is defined as finding experts in different subject areas as well as identifying people expertise area(s). For almost two decades, ER within knowledge-based environments has attracted attention of large and medium organizations. It has given rise to a strong community of researchers, especially in Computer and Information Science. It seems, however, that ER has remained neglected among Iranian researchers. So, addressing the foundations, methods and models of ER, current paper intends to take step in making scientific community and organization mangers familiar with main concepts of this area. Methodology: This paper is an opinion paper based on library method. Findings: Supporting Knowledge Management is an important application of ER systems. In these systems, by avoiding the challenging characteristics of expertise concept, researchers simplify the problem of ER and limit its scope to textual documents accumulation and discovering of documents-persons associations. Several models have been presented for discovering of above-mentioned associations, among which Balog’s models had important role in promotion of ER field. document-centric model offered by Balog and his colleagues, is one of the most successful models that is the basis for subsequent models. Originality/Value: this paper addresses the issue of Expertise Retrieval and its Foundations, methods and Models. So, it could be of interest to information professionals, Information Retrieval area researchers, large and medium organization’s managers, and other knowledge-based environments. |
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| ISSN: | 2251-8223 2251-8231 |