Cross-community context management in Cooperating Smart Spaces
Tóm tắt
Recently, social networks have become the most prevalent IT paradigm, as the vast majority of Internet users maintain one or multiple social networking accounts. These accounts, irrespectively of the underlying service, contain rich information and data for the owner’s preferences, social skills, everyday activities, beliefs and interests. Along with these services, the computation, sensing and networking capabilities of the state of the art mobile and portable devices, with their always-on mode, assist users in their everyday lives. Thus, the integration of social networking services with current pervasive computing systems could provide the users with the potential to interact with other users that have similar interests, preferences and expectations; and in general, the same or similar context, for limited or not time periods, in order to ameliorate their overall experience, communicate, socialise and improve their everyday activities with minimal effort. This paper introduces a cross-community context management framework that is suitable for Cooperating Smart Spaces, which couple the advantages of pervasive computing and social networking. This framework goes beyond the state of the art, among others, in that cross-community context from a multitude of sources is collected and processed to enhance the end user experience and increase the perceived value of the services provided.
Tài liệu tham khảo
Kietzmann J, Silvestre B, McCarthy I, Pitt L (2012) Unpacking the social media phenomenon: towards a research agenda. J Public Aff 12(2):109–119. doi:10.1002/pa.1412
Lin KY, Lu HP (2011) Why people use social networking sites: an empirical study integrating network externalities and motivation theory. Comput Hum Behav 27(3):1152–1161. doi:10.1016/j.chb.2010.12.009
Obaidat M, Denko M, Woungang I (2011) Pervasive computing networks, 1st edn. Wiley, West Sussex
Hansmann U, Merk L, Nicklous M, Stober T (2012) Pervasive computing: the mobile world, 2nd edn. Springer, Berlin
Doolin K, Roussaki I, Roddy M, Kalatzis N, Papadopoulou E, Taylor NK, Liampotis N, McKitterick D, Jennings E, Kosmides P (2012) SOCIETIES: where pervasive meets social. In: Future internet assembly book 2012, pp 30–41
Roussaki I, Kalatzis N, Liampotis N, Kosmides P, Anagnostou M, Doolin K, Jennings E, Bouloudis Y, Xynogalas S (2012) Context-awareness in wireless and mobile computing revisited to embrace social networking. Commun Mag IEEE 50(6):74–81. doi:10.1109/mcom.2012.6211489
Kang S, Kim W, Lee D, Lee Y (2005) Group context-aware service discovery for supporting continuous service availability. In: Proceedings of ubiPCMM 2005, Tokyo, Japan, pp 62–63
Marin-Perianu RS, Marin-Perianu M, Havinga PJ, Scholten J (2007) Movement-based group awareness with wireless sensor networks. In: Proceedings of pervasive 2007, Toronto, Canada, pp 298–315
Hussein T, Linder T, Gaulke W, Ziegler J (2010) A framework and an architecture for context-aware group recommendations. In: Proceedings of CRIWG 2010, Maastricht, Netherlands, pp 121–128
Bottazzi D, Corradi A, Montanari R (2005) A context-aware group management middleware to support resource sharing in MANET environments. In: Proceedings of MDM 2005, Ayia Napa, Cyprus, pp 147–151
Chong C, Nishio N (2007) GRECOM: group context management middleware for group event based services. In: Proceedings of UbiComp 2007, Innsbruck, Austria, pp 176–179
Biamino G (2011) Modeling social contexts for pervasive computing environments. In: Proceedings of PerCom 2011, IEEE, Lugano, Switzerland, pp 415–420
Beach A, Gartrell M, Akkala S, Elston J, Kelley J, Nishimoto K, Ray B, Razgulin S, Sundaresan K, Surendar B, Terada M, Han R (2008) WhozThat? Evolving an ecosystem for context-aware mobile social networks. Netw IEEE 22(4):50–55. doi:10.1109/MNET.2008.4579771
Messeguer R, Navarro L, Reyes A (2007) Group-awareness for mobile cooperative learning. In: Proceedings of WMUTE 2007, IEEE, Athens, Greece, pp 74–81
Ferscha A, Holzmann C, Oppl S (2004) Context awareness for group interaction support. In: Proceedings of MobiWac 2004, Philadelphia, PA, USA, pp 88–97
Guo B, Zhang D, Wang Z, Yu Z, Zhou X (2013) Opportunistic IoT: exploring the harmonious interaction between human and the internet of things. J Netw Comput Appl. doi:10.1016/j.jnca.2012.12.028
Jung JJ (2008) Ontology-based context synchronization for ad hoc social collaborations. Elsevier Knowledge Based System Journal 21(7):573–580. doi:10.1016/j.knosys.2008.03.015
Song J, Kim S (2008) Community based context-aware information for the intelligent personalized information service. Int J Multimed Ubiquitous Eng 3(3):23–30
Beach A, Gartrell M, Xing X, Han R, Lv Q, Mishra S, Seada K (2010) Fusing mobile, sensor, and social data to fully enable context-aware computing. In: Proceedings of HotMobile 2010, Annapolis, MD, USA, pp 60–65
Guo B, Zhang D, Yu Z, Zhou X, Zhou Z (2012) Enhancing spontaneous interaction in opportunistic mobile social networks. Commun Mob Comput 1. doi:10.1186/2192-1121-1-6
Coutand O, Droegehorn O, David K, Nurmi P, Floréen P, Kernchen R, Holtmanns S, Campadello S, Kanter T, Martin M, van Eijk R, Guarneri R (2005) Context-aware group management in mobile environments. In: Proceedings of IST summit 2005, Dresden, Germany
Roussaki I, Liampotis N, Kalatzis N, Frank K, Hayden P (2009) How to make personal smart spaces context-aware. In: Proceedings of AISB 2009, Edinburgh, Scotland, pp 26–32
Eagle N, Pentland A, Lazer D (2008) Mobile phone data for inferring social network structure. In: Social computing, behavioral modeling, and prediction. Springer, US, pp 79–88
Powers DMW (2011) Evaluation: from precision, recall and f-measure to roc, informedness, markedness & correlation. J Mach Learn Technol 2(1):37–63