Title :
Cross-community sensing and mining
Author :
Bin Guo ; Zhiwen Yu ; Daqing Zhang ; Xingshe Zhou
Author_Institution :
Sch. of Comput. Sci., Northwestern Polytech. Univ., Xi´an, China
Abstract :
With the developments in information and communications technology (ICT), people are involving in and connecting via various forms of communities in the cyber-physical space, such as online communities, opportunistic (offline) social networks, and location-based social networks. Different communities have distinct features and strengths. With humans playing the bridge role, these communities are implicitly interlinked. In contrast with the existing studies that mostly consider a single community, this article addresses the interaction among distinct communities. In particular, we present an emerging research area - cross-community sensing and mining (CSM), which aims to connect heterogeneous, cross-space communities by revealing the complex linkage and interplay among their properties and identifying human behavior patterns by analyzing the data sensed/collected from multi-community environments. The article describes and discusses the research background, characters, general framework, research challenges, as well as our practice of CSM.
Keywords :
data mining; social networking (online); CSM; complex linkage; cross-community sensing and mining; cross-space communities; human behavior pattern identification; Cellular phones; Data mining; Information technology; Internet; Mobile communication; Social network services;
Journal_Title :
Communications Magazine, IEEE
DOI :
10.1109/MCOM.2014.6871682