Link Prediction in Social Networks
Virinchi, Srinivas, Mitra, Pabitra
Produktnummer:
182e5631e40212433a96b7882a9ddd2ebb
| Autor: | Mitra, Pabitra Virinchi, Srinivas |
|---|---|
| Themengebiete: | Graph Mining Link Prediction Local Neighborhood Power Law Degree Distribution Recommender Systems |
| Veröffentlichungsdatum: | 29.01.2016 |
| EAN: | 9783319289212 |
| Sprache: | Englisch |
| Seitenzahl: | 67 |
| Produktart: | Kartoniert / Broschiert |
| Verlag: | Springer International Publishing |
| Untertitel: | Role of Power Law Distribution |
Produktinformationen "Link Prediction in Social Networks"
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.
Sie möchten lieber vor Ort einkaufen?
Sie haben Fragen zu diesem oder anderen Produkten oder möchten einfach gerne analog im Laden stöbern? Wir sind gerne für Sie da und beraten Sie auch telefonisch.
Juristische Fachbuchhandlung
Georg Blendl
Parcellistraße 5 (Maxburg)
8033 München
Montag - Freitag: 8:15 -18 Uhr
Samstags geschlossen