Ontological User Modelling and Semantic Rule-Based Reasoning for Personalisation of Help-on-Demand Services in Pervasive Environments

Kerry-Louise Skillen, Liming Chen, Christopher Nugent, Mark Donnelly, William Burns, Ivar Solheim

Research output: Contribution to journalArticle

Abstract

Existing context-aware applications are limited in their support of user personalisation. Nevertheless, the increase in the use of context-aware technologies has sparked the growth in assistive applications resulting in a need to enable adaptation to reflect the changes in user behaviors. This paper introduces a systematic approach to service personalisation for mobile users in pervasive environments and presents a service-oriented distributed system architecture. The developed approach makes use of semantic technologies for user modelling and personalisation reasoning. In the paper we characterise user behaviours and needs in pervasive environments upon which ontological user models are created with special emphasis being placed on ontological modelling of dynamic and adaptive user profiles. We develop a rule-based personalisation mechanism that exploits semantic web rule mark-up language for rule design and a combination of semantic and rule-based reasoning for personalisation. We use two case studies focusing on providing personalised travel assistance for people using Help-on-Demand services deployed on a smart-phone to contextualise the discussions within the paper. The proposed approach is implemented in a prototype system, which includes Help-on-Demand services, content management services, user models and personalisation mechanisms in addition to application specific rules. Experiments have been designed and conducted to test and evaluate the approach with initial results demonstrating the functionality of the approach.
LanguageEnglish
Pages97-109
JournalFuture Generation Computer Systems
Volume34
Early online date15 Nov 2013
DOIs
Publication statusPublished - May 2014

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Semantics
Semantic Web
Experiments

Keywords

  • Ontologies
  • user modelling
  • personalisation
  • context-awareness

Cite this

@article{00d615d8f15248059adf50f3e8612625,
title = "Ontological User Modelling and Semantic Rule-Based Reasoning for Personalisation of Help-on-Demand Services in Pervasive Environments",
abstract = "Existing context-aware applications are limited in their support of user personalisation. Nevertheless, the increase in the use of context-aware technologies has sparked the growth in assistive applications resulting in a need to enable adaptation to reflect the changes in user behaviors. This paper introduces a systematic approach to service personalisation for mobile users in pervasive environments and presents a service-oriented distributed system architecture. The developed approach makes use of semantic technologies for user modelling and personalisation reasoning. In the paper we characterise user behaviours and needs in pervasive environments upon which ontological user models are created with special emphasis being placed on ontological modelling of dynamic and adaptive user profiles. We develop a rule-based personalisation mechanism that exploits semantic web rule mark-up language for rule design and a combination of semantic and rule-based reasoning for personalisation. We use two case studies focusing on providing personalised travel assistance for people using Help-on-Demand services deployed on a smart-phone to contextualise the discussions within the paper. The proposed approach is implemented in a prototype system, which includes Help-on-Demand services, content management services, user models and personalisation mechanisms in addition to application specific rules. Experiments have been designed and conducted to test and evaluate the approach with initial results demonstrating the functionality of the approach.",
keywords = "Ontologies, user modelling, personalisation, context-awareness",
author = "Kerry-Louise Skillen and Liming Chen and Christopher Nugent and Mark Donnelly and William Burns and Ivar Solheim",
note = "Reference text: [1] Cook, D.J.; Das, S.K. How Smart are our Environments? an Updated Look at the State of the Art. Pervasive and Mobile Computing 2007, 3, 53-73. [2] Perttunen, M.; Riekki, J.; Lassila, O. Context Representation and Reasoning in Pervasive Computing: A Review. International Journal of Multimedia and Ubiquitous Engineering 2009, 4. [3] Fischer, G. User Modeling in Human\–Computer Interaction. User Modeling and User-Adapted Interaction 2001, 11, 65-86. [4] Zimmermann, A.; Specht, M.; Lorenz, A. Personalization and Context Management. User Modeling and User-Adapted Interaction 2005, 15, 275-302. [5] Roh, J.H.; Jin, S. Personalized Advertisement Recommendation System Based on User Profile in the Smart Phone. In Advanced Communication Technology (ICACT), 2012 14th International Conference On; pp. 1300- 1303. [6] Tanca, L.; Bolchini, C.; Quintarelli, E.; Schreiber, F.A.; Orsi, G. Problems and Opportunities in Context- Based Personalization. Proceedings of the VLDB Endowment 2011, 4, 1-4. [7] Abowd, G.D.; Dey, A.K.; Brown, P.J.; Davies, N.; Smith, M.; Steggles, P. Towards a Better Understanding of Context and Context-Awareness. In Handheld and Ubiquitous Computing; pp. 304-307. [8] Bettini, C.; Brdiczka, O.; Henricksen, K.; Indulska, J.; Nicklas, D.; Ranganathan, A.; Riboni, D. A Survey of Context Modelling and Reasoning Techniques. Pervasive and Mobile Computing 2010, 6, 161-180. [9] Kay, J.; McCalla, G. Coming of Age: Celebrating a Quarter Century of User Modeling and Personalization: Guest Editors’ Introduction. User Modeling and User-Adapted Interaction 2012, 22, 1-7. [10] Sutterer, M.; Droegehorn, O.; David, K. UPOS: User Profile Ontology with Situation-Dependent Preferences Support. In Advances in Computer-Human Interaction, 2008 First International Conference On; pp. 230-235. [11] Mehta, B.; Niederee, C.; Stewart, A.; Degemmis, M.; Lops, P.; Semeraro, G. Ontologically-Enriched Unified User Modeling for Cross-System Personalization. User Modeling 2005, 151-151. [12] Golemati, M.; Katifori, A.; Vassilakis, C.; Lepouras, G.; Halatsis, C. Creating an Ontology for the User Profile: Method and Applications. In Proceedings of the First RCIS Conference; pp. 407-412. [13] Kofod-Petersen, A.; Aamodt, A. Case-Based Situation Assessment in a Mobile Context-Aware System. In Proceedings of AIMS2003, Workshop on Artificial Intgelligence for Mobil Systems, Seattle. [14] Goix, L.W.; Valla, M.; Cerami, L.; Falcarin, P. Situation Inference for Mobile Users: A Rule Based Approach. In Mobile Data Management, 2007 International Conference On; pp. 299-303. [15] Chen, A. Context-Aware Collaborative Filtering System: Predicting the User’s Preference in the Ubiquitous Computing Environment. Location-and Context-Awareness 2005, 75-81. [16] Liu, C.H.; Chang, K.L.; Chen, J.J.Y.; Hung, S.C. Ontology-Based Context Representation and Reasoning using Owl and Swrl. In Communication Networks and Services Research Conference (CNSR), 2010 Eighth Annual; pp. 215-220. [17] Zhang, S.; McCullagh, P.; Nugent, C.; Zheng, H.; Black, N. An Ontological Framework for Activity Monitoring and Reminder Reasoning in an Assisted Environment. Journal of Ambient Intelligence and Humanized Computing 2011, 1-12. [18] MobileSage Group, A. MobileSage –Situated Adaptive Guidance for the Mobile Elderly. 2012, 2013, 1. [19] European Commission. Research and Innovation FP7 Project. 2012, 2013, 1. [20] Hanke, S.; Mayer, C.; Hoeftberger, O.; Boos, H.; Wichert, R.; Tazari, M.; Wolf, P.; Furfari, F. universAAL–an open and consolidated AAL platform. In Ambient Assisted Living.; Anonymous .; Springer, 2011, pp. 127-140. [21] Salvi, D.; Barsocchi, P.; Arredondo, M.T.; Ramos, J.P.L. EvAAL, evaluating AAL systems through competitive benchmarking, the experience of the 1st competition. In Evaluating AAL Systems through Competitive Benchmarking. Indoor Localization and Tracking.; Anonymous .; Springer, 2012, pp. 14-25. [22] Pan, J.; Zhang, B.; Wang, S.; Wu, G.; Wei, D. Ontology Based User Profiling in Personalized Information Service Agent. In Computer and Information Technology, 2007. CIT 2007. 7th IEEE International Conference On; pp. 1089-1093. [23] Chen, H.; Finin, T.; Joshi, A. An Ontology for Context-Aware Pervasive Computing Environments. The Knowledge Engineering Review 2003, 18, 197-207. [24] Razmerita, L.; Angehrn, A.; Maedche, A. Ontology-Based User Modeling for Knowledge Management Systems. User Modeling 2003, 148-148. [25] Viviani, M.; Bennani, N.; Egyed-Zsigmond, E. A Survey on User Modeling in Multi-Application Environments. In Advances in Human-Oriented and Personalized Mechanisms, Technologies and Services (CENTRIC), 2010 Third International Conference On; pp. 111-116. [26] Pan, R.; Ding, Z.; Yu, Y.; Peng, Y. A Bayesian Network Approach to Ontology Mapping. The Semantic Web–ISWC 2005 2005, 563-577. [27] Beynon, M.; Curry, B.; Morgan, P. The Dempster–Shafer Theory of Evidence: An Alternative Approach to Multicriteria Decision Modelling. Omega 2000, 28, 37-50. [28] Rojbi, S.; Soui, M. User Modeling and Web-Based Customazation Techniques: An Examination of the Published Literature. In Logistics (LOGISTIQUA), 2011 4th International Conference On; pp. 83-90. [29] Lee, J.; Lee, J. Context Awareness by Case-Based Reasoning in a Music Recommendation System. Ubiquitous Computing Systems 2007, 45-58. [30] Dong, F.; Zhang, L.; Hu, D.H.; Wang, C.L. A Case-Based Component Selection Framework for Mobile Context-Aware Applications. In Parallel and Distributed Processing with Applications, 2009 IEEE International Symposium On; pp. 366-373. [31] Ghosh, R.; Dekhil, M. Discovering User Profiles. In Proceedings of the 18th International Conference on World Wide Web; pp. 1233-1234. [32] Janev, V.; Vraneš, S. Applicability Assessment of Semantic Web Technologies. Information Processing & Management 2011, 47, 507-517. [33] Horrocks, I.; Patel-Schneider, P.F.; Boley, H.; Tabet, S.; Grosof, B.; Dean, M. SWRL: A Semantic Web Rule Language Combining OWL and RuleML. W3C Member submission 2004, 21, 79. [34] Tiberghien, T.; Mokhtari, M.; Aloulou, H.; Biswas, J. Semantic Reasoning in Context-Aware Assistive Environments to Support Ageing with Dementia. The Semantic Web–ISWC 2012, 212-227. [35] Chellouche, S.A.; Négru, D. Context-Aware Multimedia Services Provisioning in Future Internet using Ontology and Rules. In Under Review at the 8th International ICST Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (MobiQuitous 2011), Copenhagen, Denmark. [36] Almeida, A.; Orduña, P.; Castillejo, E.; Lopez-de-Ipiña, D.; Sacristán, M. Imhotep: An Approach to User and Device Conscious Mobile Applications. Personal and Ubiquitous Computing 2011, 15, 419-429. [37] Jorstad, I.; van Thanh, D. Service Personalisation in Mobile Heterogeneous Environments. In Telecommunications, 2006. AICT-ICIW'06. International Conference on Internet and Web Applications and Services/Advanced International Conference On; pp. 70-70. [38] Gavalas, D.; Kenteris, M. A Web-Based Pervasive Recommendation System for Mobile Tourist Guides. Personal and Ubiquitous Computing 2011, 15, 759-770. [39] Dale, O.; Solheim, I.; Halbach, T.; Schulz, T.; Spiru, L.; Turcu, I. What Seniors Want in a Mobile Help-on- Demand Service. In eTELEMED 2013, the Fifth International Conference on eHealth, Telemedicine, and Social Medicine; pp. 96-101. [40] Skillen, K.; Chen, L.; Nugent, C.D.; Donnelly, M.P.; Burns, W.; Solheim, I. Ontological user profile modeling for context-aware application personalization. In Ubiquitous Computing and Ambient Intelligence.; Anonymous .; Springer, 2012, pp. 261-268. [41] Skillen, K.; Chen, L.; Nugent, C.D.; Donnelly, M.P.; Solheim, I. A User Profile Ontology Based Approach for Assisting People with Dementia in Mobile Environments. In Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE; pp. 6390-6393. [42] Burns, W.; Chen, L.; Nugent, C.; Donnelly, M.; Skillen, K.; Solheim, I. A Conceptual Framework for Supporting Adaptive Personalized Help-on-Demand Services. In Ambient Intelligence.; Anonymous .; Springer, 2012, pp. 427-432. [43] Chandrasekaran, B.; Josephson, J.R.; Benjamins, V.R. What are Ontologies, and Why do we Need them? Intelligent Systems and Their Applications, IEEE 1999, 14, 20-26. [44] Staab, S.; Studer, R. Handbook on Ontologies.; Springer, 2009. [45] MobileSage Group, A. User Needs Analysis. 2012. [46] Horridge, M.; Knublauch, H.; Rector, A.; Stevens, R.; Wroe, C. A Practical Guide to Building OWL Ontologies using the Protégé-OWL Plugin and CO-ODE Tools Edition 1.0. University of Manchester 2004. [47] Ke{\ss}ler, C.; Raubal, M.; Wosniok, C. Semantic Rules for Context-Aware Geographical Information Retrieval. Smart Sensing and Context 2009, 77-92. [48] Sirin, E.; Parsia, B.; Grau, B.C.; Kalyanpur, A.; Katz, Y. Pellet: A Practical Owl-Dl Reasoner. Web Semantics: science, services and agents on the World Wide Web 2007, 5, 51-53. [49] Bechhofer, S.; Volz, R.; Lord, P. Cooking the Semantic Web with the OWL API. The Semantic Web-ISWC 2003 2003, 659-675.",
year = "2014",
month = "5",
doi = "10.1016/j.future.2013.10.027",
language = "English",
volume = "34",
pages = "97--109",
journal = "Future Generation Computer Systems",
issn = "0167-739X",
publisher = "Elsevier",

}

TY - JOUR

T1 - Ontological User Modelling and Semantic Rule-Based Reasoning for Personalisation of Help-on-Demand Services in Pervasive Environments

AU - Skillen, Kerry-Louise

AU - Chen, Liming

AU - Nugent, Christopher

AU - Donnelly, Mark

AU - Burns, William

AU - Solheim, Ivar

N1 - Reference text: [1] Cook, D.J.; Das, S.K. How Smart are our Environments? an Updated Look at the State of the Art. Pervasive and Mobile Computing 2007, 3, 53-73. [2] Perttunen, M.; Riekki, J.; Lassila, O. Context Representation and Reasoning in Pervasive Computing: A Review. International Journal of Multimedia and Ubiquitous Engineering 2009, 4. [3] Fischer, G. User Modeling in Human\–Computer Interaction. User Modeling and User-Adapted Interaction 2001, 11, 65-86. [4] Zimmermann, A.; Specht, M.; Lorenz, A. Personalization and Context Management. User Modeling and User-Adapted Interaction 2005, 15, 275-302. [5] Roh, J.H.; Jin, S. Personalized Advertisement Recommendation System Based on User Profile in the Smart Phone. In Advanced Communication Technology (ICACT), 2012 14th International Conference On; pp. 1300- 1303. [6] Tanca, L.; Bolchini, C.; Quintarelli, E.; Schreiber, F.A.; Orsi, G. Problems and Opportunities in Context- Based Personalization. Proceedings of the VLDB Endowment 2011, 4, 1-4. [7] Abowd, G.D.; Dey, A.K.; Brown, P.J.; Davies, N.; Smith, M.; Steggles, P. Towards a Better Understanding of Context and Context-Awareness. In Handheld and Ubiquitous Computing; pp. 304-307. [8] Bettini, C.; Brdiczka, O.; Henricksen, K.; Indulska, J.; Nicklas, D.; Ranganathan, A.; Riboni, D. A Survey of Context Modelling and Reasoning Techniques. Pervasive and Mobile Computing 2010, 6, 161-180. [9] Kay, J.; McCalla, G. Coming of Age: Celebrating a Quarter Century of User Modeling and Personalization: Guest Editors’ Introduction. User Modeling and User-Adapted Interaction 2012, 22, 1-7. [10] Sutterer, M.; Droegehorn, O.; David, K. UPOS: User Profile Ontology with Situation-Dependent Preferences Support. In Advances in Computer-Human Interaction, 2008 First International Conference On; pp. 230-235. [11] Mehta, B.; Niederee, C.; Stewart, A.; Degemmis, M.; Lops, P.; Semeraro, G. Ontologically-Enriched Unified User Modeling for Cross-System Personalization. User Modeling 2005, 151-151. [12] Golemati, M.; Katifori, A.; Vassilakis, C.; Lepouras, G.; Halatsis, C. Creating an Ontology for the User Profile: Method and Applications. In Proceedings of the First RCIS Conference; pp. 407-412. [13] Kofod-Petersen, A.; Aamodt, A. Case-Based Situation Assessment in a Mobile Context-Aware System. In Proceedings of AIMS2003, Workshop on Artificial Intgelligence for Mobil Systems, Seattle. [14] Goix, L.W.; Valla, M.; Cerami, L.; Falcarin, P. Situation Inference for Mobile Users: A Rule Based Approach. In Mobile Data Management, 2007 International Conference On; pp. 299-303. [15] Chen, A. Context-Aware Collaborative Filtering System: Predicting the User’s Preference in the Ubiquitous Computing Environment. Location-and Context-Awareness 2005, 75-81. [16] Liu, C.H.; Chang, K.L.; Chen, J.J.Y.; Hung, S.C. Ontology-Based Context Representation and Reasoning using Owl and Swrl. In Communication Networks and Services Research Conference (CNSR), 2010 Eighth Annual; pp. 215-220. [17] Zhang, S.; McCullagh, P.; Nugent, C.; Zheng, H.; Black, N. An Ontological Framework for Activity Monitoring and Reminder Reasoning in an Assisted Environment. Journal of Ambient Intelligence and Humanized Computing 2011, 1-12. [18] MobileSage Group, A. MobileSage –Situated Adaptive Guidance for the Mobile Elderly. 2012, 2013, 1. [19] European Commission. Research and Innovation FP7 Project. 2012, 2013, 1. [20] Hanke, S.; Mayer, C.; Hoeftberger, O.; Boos, H.; Wichert, R.; Tazari, M.; Wolf, P.; Furfari, F. universAAL–an open and consolidated AAL platform. In Ambient Assisted Living.; Anonymous .; Springer, 2011, pp. 127-140. [21] Salvi, D.; Barsocchi, P.; Arredondo, M.T.; Ramos, J.P.L. EvAAL, evaluating AAL systems through competitive benchmarking, the experience of the 1st competition. In Evaluating AAL Systems through Competitive Benchmarking. Indoor Localization and Tracking.; Anonymous .; Springer, 2012, pp. 14-25. [22] Pan, J.; Zhang, B.; Wang, S.; Wu, G.; Wei, D. Ontology Based User Profiling in Personalized Information Service Agent. In Computer and Information Technology, 2007. CIT 2007. 7th IEEE International Conference On; pp. 1089-1093. [23] Chen, H.; Finin, T.; Joshi, A. An Ontology for Context-Aware Pervasive Computing Environments. The Knowledge Engineering Review 2003, 18, 197-207. [24] Razmerita, L.; Angehrn, A.; Maedche, A. Ontology-Based User Modeling for Knowledge Management Systems. User Modeling 2003, 148-148. [25] Viviani, M.; Bennani, N.; Egyed-Zsigmond, E. A Survey on User Modeling in Multi-Application Environments. In Advances in Human-Oriented and Personalized Mechanisms, Technologies and Services (CENTRIC), 2010 Third International Conference On; pp. 111-116. [26] Pan, R.; Ding, Z.; Yu, Y.; Peng, Y. A Bayesian Network Approach to Ontology Mapping. The Semantic Web–ISWC 2005 2005, 563-577. [27] Beynon, M.; Curry, B.; Morgan, P. The Dempster–Shafer Theory of Evidence: An Alternative Approach to Multicriteria Decision Modelling. Omega 2000, 28, 37-50. [28] Rojbi, S.; Soui, M. User Modeling and Web-Based Customazation Techniques: An Examination of the Published Literature. In Logistics (LOGISTIQUA), 2011 4th International Conference On; pp. 83-90. [29] Lee, J.; Lee, J. Context Awareness by Case-Based Reasoning in a Music Recommendation System. Ubiquitous Computing Systems 2007, 45-58. [30] Dong, F.; Zhang, L.; Hu, D.H.; Wang, C.L. A Case-Based Component Selection Framework for Mobile Context-Aware Applications. In Parallel and Distributed Processing with Applications, 2009 IEEE International Symposium On; pp. 366-373. [31] Ghosh, R.; Dekhil, M. Discovering User Profiles. In Proceedings of the 18th International Conference on World Wide Web; pp. 1233-1234. [32] Janev, V.; Vraneš, S. Applicability Assessment of Semantic Web Technologies. Information Processing & Management 2011, 47, 507-517. [33] Horrocks, I.; Patel-Schneider, P.F.; Boley, H.; Tabet, S.; Grosof, B.; Dean, M. SWRL: A Semantic Web Rule Language Combining OWL and RuleML. W3C Member submission 2004, 21, 79. [34] Tiberghien, T.; Mokhtari, M.; Aloulou, H.; Biswas, J. Semantic Reasoning in Context-Aware Assistive Environments to Support Ageing with Dementia. The Semantic Web–ISWC 2012, 212-227. [35] Chellouche, S.A.; Négru, D. Context-Aware Multimedia Services Provisioning in Future Internet using Ontology and Rules. In Under Review at the 8th International ICST Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (MobiQuitous 2011), Copenhagen, Denmark. [36] Almeida, A.; Orduña, P.; Castillejo, E.; Lopez-de-Ipiña, D.; Sacristán, M. Imhotep: An Approach to User and Device Conscious Mobile Applications. Personal and Ubiquitous Computing 2011, 15, 419-429. [37] Jorstad, I.; van Thanh, D. Service Personalisation in Mobile Heterogeneous Environments. In Telecommunications, 2006. AICT-ICIW'06. International Conference on Internet and Web Applications and Services/Advanced International Conference On; pp. 70-70. [38] Gavalas, D.; Kenteris, M. A Web-Based Pervasive Recommendation System for Mobile Tourist Guides. Personal and Ubiquitous Computing 2011, 15, 759-770. [39] Dale, O.; Solheim, I.; Halbach, T.; Schulz, T.; Spiru, L.; Turcu, I. What Seniors Want in a Mobile Help-on- Demand Service. In eTELEMED 2013, the Fifth International Conference on eHealth, Telemedicine, and Social Medicine; pp. 96-101. [40] Skillen, K.; Chen, L.; Nugent, C.D.; Donnelly, M.P.; Burns, W.; Solheim, I. Ontological user profile modeling for context-aware application personalization. In Ubiquitous Computing and Ambient Intelligence.; Anonymous .; Springer, 2012, pp. 261-268. [41] Skillen, K.; Chen, L.; Nugent, C.D.; Donnelly, M.P.; Solheim, I. A User Profile Ontology Based Approach for Assisting People with Dementia in Mobile Environments. In Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE; pp. 6390-6393. [42] Burns, W.; Chen, L.; Nugent, C.; Donnelly, M.; Skillen, K.; Solheim, I. A Conceptual Framework for Supporting Adaptive Personalized Help-on-Demand Services. In Ambient Intelligence.; Anonymous .; Springer, 2012, pp. 427-432. [43] Chandrasekaran, B.; Josephson, J.R.; Benjamins, V.R. What are Ontologies, and Why do we Need them? Intelligent Systems and Their Applications, IEEE 1999, 14, 20-26. [44] Staab, S.; Studer, R. Handbook on Ontologies.; Springer, 2009. [45] MobileSage Group, A. User Needs Analysis. 2012. [46] Horridge, M.; Knublauch, H.; Rector, A.; Stevens, R.; Wroe, C. A Practical Guide to Building OWL Ontologies using the Protégé-OWL Plugin and CO-ODE Tools Edition 1.0. University of Manchester 2004. [47] Keßler, C.; Raubal, M.; Wosniok, C. Semantic Rules for Context-Aware Geographical Information Retrieval. Smart Sensing and Context 2009, 77-92. [48] Sirin, E.; Parsia, B.; Grau, B.C.; Kalyanpur, A.; Katz, Y. Pellet: A Practical Owl-Dl Reasoner. Web Semantics: science, services and agents on the World Wide Web 2007, 5, 51-53. [49] Bechhofer, S.; Volz, R.; Lord, P. Cooking the Semantic Web with the OWL API. The Semantic Web-ISWC 2003 2003, 659-675.

PY - 2014/5

Y1 - 2014/5

N2 - Existing context-aware applications are limited in their support of user personalisation. Nevertheless, the increase in the use of context-aware technologies has sparked the growth in assistive applications resulting in a need to enable adaptation to reflect the changes in user behaviors. This paper introduces a systematic approach to service personalisation for mobile users in pervasive environments and presents a service-oriented distributed system architecture. The developed approach makes use of semantic technologies for user modelling and personalisation reasoning. In the paper we characterise user behaviours and needs in pervasive environments upon which ontological user models are created with special emphasis being placed on ontological modelling of dynamic and adaptive user profiles. We develop a rule-based personalisation mechanism that exploits semantic web rule mark-up language for rule design and a combination of semantic and rule-based reasoning for personalisation. We use two case studies focusing on providing personalised travel assistance for people using Help-on-Demand services deployed on a smart-phone to contextualise the discussions within the paper. The proposed approach is implemented in a prototype system, which includes Help-on-Demand services, content management services, user models and personalisation mechanisms in addition to application specific rules. Experiments have been designed and conducted to test and evaluate the approach with initial results demonstrating the functionality of the approach.

AB - Existing context-aware applications are limited in their support of user personalisation. Nevertheless, the increase in the use of context-aware technologies has sparked the growth in assistive applications resulting in a need to enable adaptation to reflect the changes in user behaviors. This paper introduces a systematic approach to service personalisation for mobile users in pervasive environments and presents a service-oriented distributed system architecture. The developed approach makes use of semantic technologies for user modelling and personalisation reasoning. In the paper we characterise user behaviours and needs in pervasive environments upon which ontological user models are created with special emphasis being placed on ontological modelling of dynamic and adaptive user profiles. We develop a rule-based personalisation mechanism that exploits semantic web rule mark-up language for rule design and a combination of semantic and rule-based reasoning for personalisation. We use two case studies focusing on providing personalised travel assistance for people using Help-on-Demand services deployed on a smart-phone to contextualise the discussions within the paper. The proposed approach is implemented in a prototype system, which includes Help-on-Demand services, content management services, user models and personalisation mechanisms in addition to application specific rules. Experiments have been designed and conducted to test and evaluate the approach with initial results demonstrating the functionality of the approach.

KW - Ontologies

KW - user modelling

KW - personalisation

KW - context-awareness

U2 - 10.1016/j.future.2013.10.027

DO - 10.1016/j.future.2013.10.027

M3 - Article

VL - 34

SP - 97

EP - 109

JO - Future Generation Computer Systems

T2 - Future Generation Computer Systems

JF - Future Generation Computer Systems

SN - 0167-739X

ER -