Semantically sampling in heterogeneous social networks.
Journal
22nd International World Wide Web Conference, WWW '13, Rio de Janeiro, Brazil, May 13-17, 2013, Companion Volume
Pages
181-182
Date Issued
2013
Author(s)
Abstract
Online social networks sampling identifies a representative subnetwork that preserves certain graph property given het- erogeneous semantics, with the full network not observed during sampling. This study presents a property, Relational Profile, to account for conditional dependency of node and relation type semantics in a network, and a sampling method to preserve the property. We show the proposed sampling method better preserves Relational Profile. Next, Relational Profile can design features to boost network prediction. Fi- nally, our sampled network trains more accurate prediction models than other sampling baselines.
SDGs
Type
conference paper