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Link Prediction in Social Networks: Role of Power Law Distribution (SpringerBriefs in Computer Science)

Srinivas Virinchi, Pabitra Mitra




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 | #2886423 in Books |  2016-01-23 |  2016-02-23 | Original language:English | PDF # 1 |  9.25 x.19 x6.10l,.0 | File type: PDF | 67 pages

||About the Author||Dr. Virinchi Srinivas is a Graduate Research Assistant in the Department of Computer Science at the University of Maryland, College Park, MD, USA. |Dr. Pabitra Mitra is an Associate Professor in the Depart

This work presents link prediction similarity measures for social networks that exploit the degree distribution of the networks. In the context of link prediction in dense networks, the text proposes similarity measures based on Markov inequality degree thresholding (MIDTs), which only consider nodes whose degree is above a threshold for a possible link. Also presented are similarity measures based on cliques (CNC, AAC, RAC), which assign extra weight between nodes sh...

You easily download any file type for your device.Link Prediction in Social Networks: Role of Power Law Distribution (SpringerBriefs in Computer Science)   |  Srinivas Virinchi, Pabitra Mitra. I have read it a couple of times and even shared with my family members. Really good. Couldnt put it down.

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