DocumentCode :
1608245
Title :
"Read" More from Business Cards: Toward a Smart Social Contact Management System
Author :
Guo, Bin ; Zhang, Daqing ; Yang, Dingqi
Author_Institution :
Telecom SudParis, Inst. Telecom, Evry, France
Volume :
1
fYear :
2011
Firstpage :
384
Lastpage :
387
Abstract :
The ability to leverage the power of a network of social contacts is important to get things done. However, as the number of contacts increases, people often find it difficult to maintain their contact network by using merely memory, and are frequently encompassed with questions like "who is that person, I met him in Tokyo last year". Existing contact tools make up for the shortage of unreliable human memory by storing contact information in the digital format, but laying much burden on users on manually inputting contact data. This paper, however, presents a social contact management system called SCM, which supports the auto-collection of rich contact data by exploring the aggregated power of pervasive sensing and Web intelligence techniques. Regarding that people often need to leverage several associated things (e.g., meeting location) to fetch other information about a contact (e.g., his name), we also develop an associative contact retrieval method. The effectiveness and runtime performance of our system is validated through a set of experiments.
Keywords :
Internet; content management; information retrieval; social networking (online); ubiquitous computing; Web intelligence technique; associative contact retrieval method; business cards; contact information storage; contact tools; pervasive sensing technique; smart social contact management system; Business; Context; Data mining; Feature extraction; Humans; Sensors; Web pages; HCI; Information Integration; Pervasive Computing; Social Contact Management; Web Intelligence;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Web Intelligence and Intelligent Agent Technology (WI-IAT), 2011 IEEE/WIC/ACM International Conference on
Conference_Location :
Lyon
Print_ISBN :
978-1-4577-1373-6
Electronic_ISBN :
978-0-7695-4513-4
Type :
conf
DOI :
10.1109/WI-IAT.2011.22
Filename :
6038700
Link To Document :
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