TY - GEN
T1 - UCWW semantic-based service recommendation framework
AU - Zhang, Haiyang
AU - Nikolov, Nikola S.
AU - Ganchev, Ivan
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2016/3/22
Y1 - 2016/3/22
N2 - Context-aware recommendation systems make recommendations by adapting to user's specific situation, and thus by exploring both the user preferences and the environment. In this paper, we propose a context-aware service recommendation framework utilising semantic knowledge in the Ubiquitous Consumer Wireless World (UCWW). The main objective of the framework is to provide users with the 'best' service instances that match their dynamic, contextualised and personalised requirements and expectations, thereby aligning to the always best connected and best served (ABC&S) paradigm. In the proposed framework, services and their related attributes are modeled dynamically as a heterogeneous network, based on a given network schema. Then, profile kernels - referring to the minimal set of features describing the user preferences - are extracted to model the user profiles. Subsequently, a recommendation engine, considering both the user profiles and current context, is applied to recommend 'best' service instances to users.
AB - Context-aware recommendation systems make recommendations by adapting to user's specific situation, and thus by exploring both the user preferences and the environment. In this paper, we propose a context-aware service recommendation framework utilising semantic knowledge in the Ubiquitous Consumer Wireless World (UCWW). The main objective of the framework is to provide users with the 'best' service instances that match their dynamic, contextualised and personalised requirements and expectations, thereby aligning to the always best connected and best served (ABC&S) paradigm. In the proposed framework, services and their related attributes are modeled dynamically as a heterogeneous network, based on a given network schema. Then, profile kernels - referring to the minimal set of features describing the user preferences - are extracted to model the user profiles. Subsequently, a recommendation engine, considering both the user profiles and current context, is applied to recommend 'best' service instances to users.
KW - Ubiquitous Consumer Wireless World (UCWW)
KW - context-aware recommendation
KW - heterogeneous service network
KW - semantic-based recommendation
KW - service recommendation framework
UR - http://www.scopus.com/inward/record.url?scp=84965121052&partnerID=8YFLogxK
U2 - 10.1109/ISTAS.2015.7439435
DO - 10.1109/ISTAS.2015.7439435
M3 - Conference Proceeding
AN - SCOPUS:84965121052
T3 - International Symposium on Technology and Society, Proceedings
BT - 2015 IEEE International Symposium on Technology and Society, ISTAS 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - IEEE International Symposium on Technology and Society, ISTAS 2015
Y2 - 11 November 2015 through 12 November 2015
ER -