Identification of the CIRP expertise network based on public data
| Autor: | Rok Vrabič, L. Taner Tunç, Andreja Malus, Peter Butala, Dominik Kozjek, Erdem Ozturk |
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| Přispěvatelé: | Kjellberg, T., Wang, L., Ji, W., Wang, X. V. |
| Rok vydání: | 2018 |
| Předmět: |
Computer science
Social activity 020206 networking & telecommunications Unstructured data 02 engineering and technology Structuring Data science T175 Industrial research. Research and development Identification (information) Professional networks T58.5 Information technology 020204 information systems 0202 electrical engineering electronic engineering information engineering General Earth and Planetary Sciences Web crawler General Environmental Science |
| Zdroj: | Procedia CIRP. 72:165-168 |
| ISSN: | 2212-8271 |
| DOI: | 10.1016/j.procir.2018.03.107 |
| Popis: | Identification of expertise of people, academic societies, companies, and institutions is an important professional and social activity for nurturing professional networks, forming project consortia, etc. Today, a lot of information about the skills and expertise is openly available from websites and public personal profiles on professional and scientific social networks. With computerised methods, such as web crawling, text mining, and keyword classification, it is possible to identify expertise networks from the raw unstructured data. The paper presents and analyses the extended expertise network of the CIRP scientific community and proposes a web-based tool for the structuring and management of the community’s expertise. |
| Databáze: | OpenAIRE |
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