Rehman, Muhammad Zubair and Kamal Zuhairi, Zamli and Almutairi, Mubarak and Chiroma, Haruna and Aamir, Muhammad and Kader, Md. Abdul and Nazri, Mohd. Nawi (2021) A novel state space reduction algorithm for team formation in social networks. PLoS ONE, 16 (12). pp. 1-18. ISSN 1932-6203. (Published)
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Abstract
Team formation (TF) in social networks exploits graphs (i.e., vertices = experts and edges = skills) to represent a possible collaboration between the experts. These networks lead us towards building cost-effective research teams irrespective of the geolocation of the experts and the size of the dataset. Previously, large datasets were not closely inspected for the large-scale distributions & relationships among the researchers, resulting in the algorithms failing to scale well on the data. Therefore, this paper presents a novel TF algorithm for expert team formation called SSR-TF based on two metrics; communication cost and graph reduction, that will become a basis for future TF’s. In SSR-TF, communication cost finds the possibility of collaboration between researchers. The graph reduction scales the large data to only appropriate skills and the experts, resulting in real-time extraction of experts for collaboration. This approach is tested on five organic and benchmark datasets, i.e., UMP, DBLP, ACM, IMDB, and Bibsonomy. The SSR-TF algorithm is able to build cost-effective teams with the most appropriate experts–resulting in the formation of more communicative teams with high expertise levels.
| Item Type: | Article |
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| Additional Information: | Indexed by Scopus |
| Uncontrolled Keywords: | Algorithm; Article; Extraction; Human; Skill; Social network |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software |
| Faculty/Division: | Institute of Postgraduate Studies Faculty of Computing |
| Depositing User: | Mr Muhamad Firdaus Janih@Jaini |
| Date Deposited: | 31 May 2022 02:03 |
| Last Modified: | 31 May 2022 02:03 |
| URI: | http://umpir.ump.edu.my/id/eprint/33087 |
| Download Statistic: | View Download Statistics |
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