Online-Ressource
Verfasst von:	Srinivas, Virinchi
Titel:	Link Prediction in Social Networks
Titelzusatz:	Role of Power Law Distribution
Mitwirkende:	Mitra, Pabitra
Verf.angabe:	by Virinchi Srinivas, Pabitra Mitra
Ausgabe:	1st ed. 2016
Verlagsort:	Cham
Verlag:	Springer International Publishing
Jahr:	2016
Umfang:	Online-Ressource (IX, 67 p. 5 illus. in color, online resource)
Gesamttitel/Reihe:	SpringerBriefs in Computer Science
	SpringerLink : Bücher
ISBN:	978-3-319-28922-9
Abstract:	Introduction -- Link Prediction Using Degree Thresholding -- Locally Adaptive Link Prediction -- Two Phase Framework for Link Prediction -- Applications of Link Prediction -- Conclusion.
	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.
DOI:	doi:10.1007/978-3-319-28922-9
URL:	Volltext ; Resolving-System: https://doi.org/10.1007/978-3-319-28922-9
	Volltext: http://dx.doi.org/10.1007/978-3-319-28922-9
	Cover ; Verlag: https://swbplus.bsz-bw.de/bsz455230358cov.jpg
	Inhaltstext: https://zbmath.org/?q=an:1358.68008
	DOI: https://doi.org/10.1007/978-3-319-28922-9
Schlagwörter:	(s)Rechnernetz    / (s)Computerunterstützte Kommunikation    / (s)Informatik    / (s)Data Mining    / (s)Wissensextraktion    / (s)Soziales Netzwerk    / (s)Potenzialanalyse
Datenträger:	Online-Ressource
Sprache:	eng
Reproduktion:	Druckausg
RVK-Notation:	ST 530
K10plus-PPN:	1654794635
	Universitätsbibliothek
Lokale URL UB:	Zum Volltext
	Bibliothek der Medizinischen Fakultät Mannheim der Universität Heidelberg
	Bestellen/Vormerken für Benutzer des Klinikums Mannheim Eigene Kennung erforderlich
Bibliothek/Idn:	UW / m3375671113
Lokale URL Inst.:	Zum Volltext