Research on social network discovery algorithm in pervasive sensing environment

Abstract

SUMMARYConsidering the real social community network partition approach regardless of the directed and weighted characteristic, we propose a novel algorithm in pervasive sensing environment. The proposed SDOR algorithm is based on the definition of nodes optimal route, community likeness index, community discrete degree index and so on parameters to achieve the sensible partition for directed weighted social community network. We conduct some different types of experiments to verify the scalability, accuracy, and validity of the proposed algorithm. The experimental consequences demonstrate that the accuracy of the algorithm is about 90%, higher than existing models about 10%. In addition, the algorithm has good effectiveness and scalability in other different kinds of network.

Big data‐related technologies and applications

“…M. Xie studied meta‐analytically integrated results from piles of network position researches in organizational innovation in 20 years. Considering the real social community network partition approach regardless of the directed and weighted characteristic, K. Gao proposed a novel algorithm in pervasive sensing environment. Start with classifying and comparing current search engines, particularly from the perspective of search patterns which consist of index structure, user profiles, and interaction mechanism.…”