TY - GEN
T1 - System design for estimating social relationships from sensing data
AU - Kida, Akihiro
AU - Takahashi, Tatsuro
AU - Shinkuma, Ryoichi
AU - Kasai, Hiroyuki
AU - Yamaguchi, Kazuhiro
AU - Mayora, Oscar
PY - 2013
Y1 - 2013
N2 - As the number of network services provided in fixed and mobile environments are increasing recently, it becomes harder to expect users to manually pick up appropriate services from all these available. Therefore, it has been proposed that network services are automatically selected in accordance with relational information among people and other social objects, i.e., locations, things and contents. The fusion of online and physical sensing platforms has brought about the possibility of building relational information from sensing data: online logs and sensing data collected at mobile devices could reflect what objects people are related to in their daily lives. The relational information can be represented as a graph in which each node could be a social object and each link could represent a direct relation between two nodes and is called relational metric. We discuss how to build relational metrics from sensing data and propose a system design for it.
AB - As the number of network services provided in fixed and mobile environments are increasing recently, it becomes harder to expect users to manually pick up appropriate services from all these available. Therefore, it has been proposed that network services are automatically selected in accordance with relational information among people and other social objects, i.e., locations, things and contents. The fusion of online and physical sensing platforms has brought about the possibility of building relational information from sensing data: online logs and sensing data collected at mobile devices could reflect what objects people are related to in their daily lives. The relational information can be represented as a graph in which each node could be a social object and each link could represent a direct relation between two nodes and is called relational metric. We discuss how to build relational metrics from sensing data and propose a system design for it.
KW - filter design
KW - network formation
KW - social closeness
KW - social network
UR - http://www.scopus.com/inward/record.url?scp=84881465590&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84881465590&partnerID=8YFLogxK
U2 - 10.1109/WAINA.2013.103
DO - 10.1109/WAINA.2013.103
M3 - Conference contribution
AN - SCOPUS:84881465590
SN - 9780769549521
T3 - Proceedings - 27th International Conference on Advanced Information Networking and Applications Workshops, WAINA 2013
SP - 27
EP - 32
BT - Proceedings - 27th International Conference on Advanced Information Networking and Applications Workshops, WAINA 2013
T2 - 27th International Conference on Advanced Information Networking and Applications Workshops, WAINA 2013
Y2 - 25 March 2013 through 28 March 2013
ER -