Please use this identifier to cite or link to this item: https://idr.l2.nitk.ac.in/jspui/handle/123456789/7339
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dc.contributor.authorAsiwal, K.-
dc.contributor.authorSuresh, B.K.-
dc.contributor.authorRam Mohana Reddy, Guddeti-
dc.date.accessioned2020-03-30T09:58:52Z-
dc.date.available2020-03-30T09:58:52Z-
dc.date.issued2016-
dc.identifier.citationCommunications in Computer and Information Science, 2016, Vol.618, , pp.8-14en_US
dc.identifier.urihttps://idr.nitk.ac.in/jspui/handle/123456789/7339-
dc.description.abstractSocial network analysis has been used for decades to find behavioral patterns and relationships that exist between people in a network. Researchers have been collaborating for centuries with the aim of improving the quality of research, to broaden the scope of problems that they tackle, to speed up the output and to disseminate knowledge across authors. Sometimes it becomes difficult to find the right collaboration partner due to various reasons, the major one being the lack of data about individuals working in their chosen domain in geographically separated locations. In this paper, we explain how social network analysis can be used to help researchers in finding suitable collaboration partners with whom they have not worked in the past but can collaborate in the future. Further, we have considered two different analysis techniques � weighted and nonweighted graph and the results are compared based on the relevance of the outcomes. � Springer International Publishing Switzerland 2016.en_US
dc.titleAnalysis of academic research networks to find collaboration partnersen_US
dc.typeBook chapteren_US
Appears in Collections:2. Conference Papers

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