Description: Link Prediction in Social Networks : Role of Power Law Distribution, Paperback by Srinivas, Virinchi; Mitra, Pabitra, ISBN 3319289217, ISBN-13 9783319289212, Like New Used, Free shipping in the US Thiswork presents link prediction similarity measures for social networks that exploitthe degree distribution of the networks. In the context of link prediction indense networks, the text proposes similarity measures based on Markov inequalitydegree thresholding (MIDTs), which only consider nodes whose degree is above a thresholdfor a possible link. Also presented are similarity measures based on cliques(CNC, AAC, RAC), which assign extra weight between nodes sharing a greater numberof cliques. Additionally, a locally adaptive (LA) similarity measure isproposed that assigns different weights to common nodes based on the degreedistribution of the local neighborhood and the degree distribution of thenetwork. In the context of link prediction in dense networks, the textintroduces a novel two-phase framework that adds edges to the sparse graph toforma boost graph.
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Book Title: Link Prediction in Social Networks : Role of Power Law Distributi
Number of Pages: IX, 67 Pages
Language: English
Publication Name: Link Prediction in Social Networks : the Role of Power Law Distribution
Publisher: Springer International Publishing A&G
Subject: Probability & Statistics / General, Networking / General, General, Databases / Data Mining
Publication Year: 2016
Item Weight: 47.9 Oz
Type: Textbook
Subject Area: Mathematics, Computers, Social Science
Author: Virinchi Srinivas, Pabitra Mitra
Item Length: 9.3 in
Item Width: 6.1 in
Series: Springerbriefs in Computer Science Ser.
Format: Trade Paperback
