TY - GEN
T1 - Info-bead group modeling in a mobile scenario
AU - Kuflik, Tsvi
AU - Mumblat, Yevgeni
AU - Variat, Yuri
AU - Dim, Eyal
N1 - Publisher Copyright:
© 2016 ACM.
PY - 2016/9/6
Y1 - 2016/9/6
N2 - The mobile scenario is an extremely challenging one when it comes to providing personalized, context aware services to mobile users. Users may dynamically and continuously enter and leave smart environments that may offer them relevant services. However, the environments may not know anything about the users and hence, providing personalized, context aware services becomes a challenge: users need to be identified, queried for their preferences and monitored before a service can be provided. The lack of standard, easy to use personalization infrastructure worsens the problem - every service provider needs to build a proprietary, add-hoc user modeling component from scratch, thus to invest considerable effort in the task. This work builds on top of previous work on Info-Beads user modeling. Following past research, it suggests an Info-Beads approach for mobile user modeling for monitoring users and enabling standardization in building user models, reusing both components and data. The specific contribution is to allow monitoring mobile users, reasoning on their data and creating individual and group models from it. We demonstrate the ideas in the area of media content recommendations for groups and individual mobile users in smart environments, as a possible case study.
AB - The mobile scenario is an extremely challenging one when it comes to providing personalized, context aware services to mobile users. Users may dynamically and continuously enter and leave smart environments that may offer them relevant services. However, the environments may not know anything about the users and hence, providing personalized, context aware services becomes a challenge: users need to be identified, queried for their preferences and monitored before a service can be provided. The lack of standard, easy to use personalization infrastructure worsens the problem - every service provider needs to build a proprietary, add-hoc user modeling component from scratch, thus to invest considerable effort in the task. This work builds on top of previous work on Info-Beads user modeling. Following past research, it suggests an Info-Beads approach for mobile user modeling for monitoring users and enabling standardization in building user models, reusing both components and data. The specific contribution is to allow monitoring mobile users, reasoning on their data and creating individual and group models from it. We demonstrate the ideas in the area of media content recommendations for groups and individual mobile users in smart environments, as a possible case study.
KW - Group modeling
KW - Info-Bead
KW - Info-Bead group modeling
KW - Info-Bead user modeling
KW - Mobile user modeling
KW - User modeling
UR - http://www.scopus.com/inward/record.url?scp=84991088906&partnerID=8YFLogxK
U2 - 10.1145/2957265.2961849
DO - 10.1145/2957265.2961849
M3 - Conference contribution
AN - SCOPUS:84991088906
T3 - Proceedings of the 18th International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct, MobileHCI 2016
SP - 682
EP - 689
BT - Proceedings of the 18th International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct, MobileHCI 2016
PB - Association for Computing Machinery, Inc
T2 - 18th International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI 2016
Y2 - 6 September 2016 through 9 September 2016
ER -