Account
Orders
Advanced search
Role of Power Law Distribution
Louise Reader
Read on Louise Reader App.
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 sharing a greater number of cliques. Additionally, a locally adaptive (LA) similarity measure is proposed that assigns different weights to common nodes based on the degree distribution of the local neighborhood and the degree distribution of the network. In the context of link prediction in dense networks, the text introduces a novel two-phase framework that adds edges to the sparse graph to forma boost graph.
Les livres numériques peuvent être téléchargés depuis l'ebookstore Numilog ou directement depuis une tablette ou smartphone.
PDF : format reprenant la maquette originale du livre ; lecture recommandée sur ordinateur et tablette EPUB : format de texte repositionnable ; lecture sur tous supports (ordinateur, tablette, smartphone, liseuse)
DRM Adobe LCP
LCP DRM Adobe
This ebook is DRM protected.
LCP system provides a simplified access to ebooks: an activation key associated with your customer account allows you to open them immediately.
ebooks downloaded with LCP system can be read on:
Adobe DRM associates a file with a personal account (Adobe ID). Once your reading device is activated with your Adobe ID, your ebook can be opened with any compatible reading application.
ebooks downloaded with Adobe DRM can be read on:
mobile-and-tablet To check the compatibility with your devices,see help page
Sign up to get our latest ebook recommendations and special offers