TY - GEN
T1 - An intelligent touring system based on mobile social network and cloud computing for travel recommendation
AU - Yu, Yuan Tse
AU - Huang, Chung Ming
AU - Lee, Yun Tz
PY - 2014
Y1 - 2014
N2 - Although many travel recommendation systems are worked with mobile social network, the articles and delivered messages between users are still not to be utilized well for estimating user preferences. If the articles and the delivered messages are closed related with the touring experiences, the information should be merged to the recommendation systems. Therefore, the information can be used for generating recommendation POIs through the intelligent modules. Besides, if the groups of social network and the exchanged information are collected large enough, the generating POIs should be more closed to user preferences. But the ideal situations are still not provided on the developed traveling recommendation system of current Internet. Therefore, we proposed a cloud-based Intelligent Touring System (ITS) to provide personalized PoIs instantly. By combining developed cloud computing technology, we can achieve analyzing posted blogs in mobile social network and recognizing user pedestrian patterns through smart phone sensors. Afterward, in order to generate the suggested PoIs related with user preferences, we construct meta-group based on similar user preferences. Moreover, in order to achieve meta-group classification, we developed clustering algorithm based on CLOPE [8]. Finally, we conducted experiments for examining the performance of the proposed meta-group classification, and the results show it could construct groups with similar preferences and provide suitable PoIs to users during touring.
AB - Although many travel recommendation systems are worked with mobile social network, the articles and delivered messages between users are still not to be utilized well for estimating user preferences. If the articles and the delivered messages are closed related with the touring experiences, the information should be merged to the recommendation systems. Therefore, the information can be used for generating recommendation POIs through the intelligent modules. Besides, if the groups of social network and the exchanged information are collected large enough, the generating POIs should be more closed to user preferences. But the ideal situations are still not provided on the developed traveling recommendation system of current Internet. Therefore, we proposed a cloud-based Intelligent Touring System (ITS) to provide personalized PoIs instantly. By combining developed cloud computing technology, we can achieve analyzing posted blogs in mobile social network and recognizing user pedestrian patterns through smart phone sensors. Afterward, in order to generate the suggested PoIs related with user preferences, we construct meta-group based on similar user preferences. Moreover, in order to achieve meta-group classification, we developed clustering algorithm based on CLOPE [8]. Finally, we conducted experiments for examining the performance of the proposed meta-group classification, and the results show it could construct groups with similar preferences and provide suitable PoIs to users during touring.
UR - http://www.scopus.com/inward/record.url?scp=84904461406&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84904461406&partnerID=8YFLogxK
U2 - 10.1109/WAINA.2014.12
DO - 10.1109/WAINA.2014.12
M3 - Conference contribution
AN - SCOPUS:84904461406
SN - 9781479926527
T3 - Proceedings - 2014 IEEE 28th International Conference on Advanced Information Networking and Applications Workshops, IEEE WAINA 2014
SP - 19
EP - 24
BT - Proceedings - 2014 IEEE 28th International Conference on Advanced Information Networking and Applications Workshops, IEEE WAINA 2014
PB - IEEE Computer Society
T2 - 28th IEEE International Conference on Advanced Information Networking and Applications Workshops, IEEE WAINA 2014
Y2 - 13 May 2014 through 16 May 2014
ER -