Title
Semantically Modeling Mobile Phone Data for Urban Computing
Abstract
Urban computing aims to enhance both human life and urban environment smartly by deeply understanding human behavior occurring in urban area. Nowadays, mobile phones are often used as an attractive option for large-scale sensing of human behavior, providing a source of real and reliable data for urban computing. But analyzing the data also faces some challenges (e.g., the related data is heterogeneous and very big), and the general approaches cannot deal with them efficiently. In this paper, aiming to tackle these challenges and conduct urban computing efficiently, we propose a data integration model for the multi-source heterogeneous data related to mobile phones by using semantic technology and develop a semantic mobile data management system.
Year
DOI
Venue
2013
10.1007/978-3-319-02750-0_21
AMT
Field
DocType
Volume
Data integration,Data mining,World Wide Web,Semantic technology,Computer science,Urban environment,SPARQL,Urban computing,Mobile phone,Urban area,RDF
Conference
8210 LNCS
Issue
ISSN
Citations 
null
16113349
0
PageRank 
References 
Authors
0.34
9
4
Name
Order
Citations
PageRank
Hui Wang101.01
Zhisheng Huang298995.29
Ning Zhong32907300.63
Jiajin Huang46915.70