Abstract
Mobile devices such as cell phone, PDA and smart phone have been so popularized that they are to be a necessity for everyday life. These mobile devices can be very useful tools to collect users' life-logs because they have many sensors and users always carry them. Therefore, many studies using mobile life-logs are actually being conducted. Mobile life-logs include interaction information between users as well as personal information of each user. We collect these mobile life-logs, and additionally, high-level logs such as activity and emotion as helping users to annotate them. Based on these life-logs, we build a novel mobile social network by mining semantic relations between users in life-logs using Bayesian network. For experiments, we build the mobile social networks and analyze them. Finally, we discuss how this mobile social network can be used for practical application and implemented a proof-of-concept application.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - SocialCom 2010 |
| Subtitle of host publication | 2nd IEEE International Conference on Social Computing, PASSAT 2010: 2nd IEEE International Conference on Privacy, Security, Risk and Trust |
| Pages | 401-406 |
| Number of pages | 6 |
| DOIs | |
| Publication status | Published - 2010 Nov 29 |
| Event | 2nd IEEE International Conference on Social Computing, SocialCom 2010, 2nd IEEE International Conference on Privacy, Security, Risk and Trust, PASSAT 2010 - Minneapolis, MN, United States Duration: 2010 Aug 20 → 2010 Aug 22 |
Publication series
| Name | Proceedings - SocialCom 2010: 2nd IEEE International Conference on Social Computing, PASSAT 2010: 2nd IEEE International Conference on Privacy, Security, Risk and Trust |
|---|
Other
| Other | 2nd IEEE International Conference on Social Computing, SocialCom 2010, 2nd IEEE International Conference on Privacy, Security, Risk and Trust, PASSAT 2010 |
|---|---|
| Country | United States |
| City | Minneapolis, MN |
| Period | 10/8/20 → 10/8/22 |
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All Science Journal Classification (ASJC) codes
- Computer Networks and Communications
- Computer Science Applications
- Information Systems
Cite this
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Building mobile social network with semantic relation using bayesian network-based life-log mining. / Park, Han Saem; Cho, Sung-Bae.
Proceedings - SocialCom 2010: 2nd IEEE International Conference on Social Computing, PASSAT 2010: 2nd IEEE International Conference on Privacy, Security, Risk and Trust. 2010. p. 401-406 5591267 (Proceedings - SocialCom 2010: 2nd IEEE International Conference on Social Computing, PASSAT 2010: 2nd IEEE International Conference on Privacy, Security, Risk and Trust).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Building mobile social network with semantic relation using bayesian network-based life-log mining
AU - Park, Han Saem
AU - Cho, Sung-Bae
PY - 2010/11/29
Y1 - 2010/11/29
N2 - Mobile devices such as cell phone, PDA and smart phone have been so popularized that they are to be a necessity for everyday life. These mobile devices can be very useful tools to collect users' life-logs because they have many sensors and users always carry them. Therefore, many studies using mobile life-logs are actually being conducted. Mobile life-logs include interaction information between users as well as personal information of each user. We collect these mobile life-logs, and additionally, high-level logs such as activity and emotion as helping users to annotate them. Based on these life-logs, we build a novel mobile social network by mining semantic relations between users in life-logs using Bayesian network. For experiments, we build the mobile social networks and analyze them. Finally, we discuss how this mobile social network can be used for practical application and implemented a proof-of-concept application.
AB - Mobile devices such as cell phone, PDA and smart phone have been so popularized that they are to be a necessity for everyday life. These mobile devices can be very useful tools to collect users' life-logs because they have many sensors and users always carry them. Therefore, many studies using mobile life-logs are actually being conducted. Mobile life-logs include interaction information between users as well as personal information of each user. We collect these mobile life-logs, and additionally, high-level logs such as activity and emotion as helping users to annotate them. Based on these life-logs, we build a novel mobile social network by mining semantic relations between users in life-logs using Bayesian network. For experiments, we build the mobile social networks and analyze them. Finally, we discuss how this mobile social network can be used for practical application and implemented a proof-of-concept application.
UR - http://www.scopus.com/inward/record.url?scp=78649311660&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=78649311660&partnerID=8YFLogxK
U2 - 10.1109/SocialCom.2010.64
DO - 10.1109/SocialCom.2010.64
M3 - Conference contribution
AN - SCOPUS:78649311660
SN - 9780769542119
T3 - Proceedings - SocialCom 2010: 2nd IEEE International Conference on Social Computing, PASSAT 2010: 2nd IEEE International Conference on Privacy, Security, Risk and Trust
SP - 401
EP - 406
BT - Proceedings - SocialCom 2010
ER -