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ALAN MODELİNİN POLİTİKA KULLANILARAK KİŞİSELLEŞTİRİLMESİ

PERSONALIZING DOMAIN MODEL BY USING POLICY

Journal Name:

Publication Year:

DOI: 
10.5505/pajes.2014.96158
Abstract (2. Language): 
Nowadays, the information that can be accessed online is increasing exponentially. However, this increase in the amount of information brings difficulties to users to access information relevant with their preferences in an effective way. These difficulties could be overcomed with providing customized information or service to an individual by using personalization approach. Profiling is the basis of personalization approach and the representation of person specific information. In a user-adaptive system, personalized results will be reached according to the user’s needs after a profile specific search. In this work, semantically rich profiles are created to present personal context and developed user profiles are integrated with policies to provide a rule-based personalization. Thus, personalized information will be achieved in an effective way through profile based constraints.
Abstract (Original Language): 
Günümüzde, çevrimiçi olarak erişilen bilgi üstsel olarak artmaktadır. Bilgi miktarındaki bu artış, kullanıcıların tercihleri ile uyumlu bilgiye etkin bir şekilde erişmesini zorlaştırmaktadır. Bu zorluklar, kişiselleştirme yaklaşımı kullanılarak, bireye özel bilginin ya da servisin sunulması ile aşılabilir. Kişiselleştirme yaklaşımının temeli, kişiye özel bilgiyi temsil eden profil yapısıdır. Kullanıcı-uyarlanabilir bir sistemde, profil tipine özgü bir aramanın sonucunda, kullanıcı ihtiyaçlarına göre kişiselleştirilmiş sonuçlara ulaşılacaktır. Bu çalışmada, kişisel içeriğin sunulması amacı ile anlamsal olarak zengin profiller oluşturulmakta ve geliştirilen kullanıcı profilleri, politikalar ile entegre edilerek kural-tabanlı bir kişiselleştirme sağlanmaktadır. Böylelikle, profili temel alan kısıtlar yardımı ile kişiselleştirilmiş bilgiye erişim etkin bir şekilde gerçekleştirilecektir.
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REFERENCES

References: 

[1] OMG's Meta Object Facility (MOF). http://www.omg.org/spec/MOF/2.4.1/ (26 Ekim 2015).
[2] Brickley D, Friend-of-A-Friend (FOAF). https://www.foaf-project.org (20 Ocak 2014).
[3] Kagal L, Finin T, Joshi A. “A Policy Language for a Pervasive Computing Environment”. In IEEE 4th International Workshop on Policies for Distributed Systems and Networks, 63-74. 4-6 June, 2003.
[4] Protégé Ontoloji Editörü. http://protege.stanford.edu/ (20 Ocak 2014).
[5] FatSecret, Calories Nutrition All Things about food and diet. https://www.fatsecret.com/calories-nutrition (20 Ocak 2014).
[6] SPARQL Query Language for RDF. https://www.w3.org/TR/rdf-sparql-query (20 Ocak 2014).
[7] Ameen A, Ur Rahman Khan K, Rani BP. “Semantic Web Personalization: A Survey”. Information and Knowledge Management, 2(6), 95-105, 2012.
[8] Baldoni M, Baroglio C, Henze N. “Personalization for the Semantic Web”. In Proceedings of the First International Conference on Reasoning Web (REWERSE 2005), LNCS, (3564), 173-212, 2005.
[9] Durao F, Dolog P, Jahn K. “State of the Art: Personalization”. Knowledge in a Wiki Project, 2008.
[10] Chen H, Perich F, Chakraborty D, Finin T, Joshi A. “Intelligent Agents Meet Semantic Web in a Smart Meeting Room”. In Proceedings of the 3rd International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2004), Washington DC, USA, 2004.
[11] Middleton SE, Shadbolt NR, De Roure DC. “Ontological User Profiling in Recommender Systems”. ACM Transactions on Information Systems, 22(1), 54-88, 2004.
[12] Leung KWT, Lee DL, Lee Wang-Chien, “Personalized Web Search with Location Preferences”. IEEE 26th International Conference on Data Engineering (ICDE), Long Beach California, USA. 1-6 March 2010.
[13] Skillen KL, Chen L, Nugent CD, Donnelly MP, Burns W, Solheim I. “Ontological User Profile Modeling for Context-Aware Application Personalization”. UCAmI'12 Proceedings of the 6th International Conference on Ubiquitous Computing and Ambient Intelligence, Vitoria-Gasteiz, Spain, 3-5 December 2012.
[14] Tapucu D, Can O, Bursa O, Unalir MO. “Metamodeling Approach to Preference Management in the Semantic Web”. 4th Multidisciplinary Workshop on Advances in Preference Handling (M-PREF 2008) (In conjunction with AAAI 2008), Chicago, Illinois, USA, 13-14 July 2008.
[15] Royer JC, Willrich R, Diaz M. “User Profile-Based Authorization Policies for Network QoS Services”. Seventh IEEE International Symposium on Network Computing and Applications, Cambridge, Massachusetts, USA, 10-12 July 2008.
[16] Iqbal Z, Noll J. “Toward User-Centric Privacy-Aware User Profile Ontology for Future Services”. Third International Conference on Communication Theory, Reliability, and Quality of Service (CTRQ), Athens, TBD, Greece, 13-19 June 2010.
[17] Agostini A, Bettini C, Cesa-Bianchi N, Maggiorini D, Riboni D. “Integrated Profile and Policy Management for Mobile-Oriented Internet Services”. Technical Report Firb-Web-Minds N. TR-WEBMINDS-04, Milan, Italy, 2003.
[18] Can O, Bursa O, Unalir MO. “Personalizable Ontology-Based Access Control”. Gazi University Journal of Science, 23(4), 465-474, 2010,
[19] Uszok A, Bradshaw JM, Jeffers R. “KAoS: A Policy and Domain Services Framework for Grid Computing and Semantic Web Services”. In Trust Management (iTrust 2004), Volume 2995 of Lecture Notes in Computer Science, Oxford, UK, 29 March-1 April, 2004.
[20] Dulay N, Lupu E, Sloman M, Damianou N. “A Policy Deployment Model for the Ponder Language”. In Proceedings of IEEE/IFIP International Symposium on Integrated Network Management (IM 2001), UK, May 2001.
[21] Tonti G, Bradshaw JM, Jeffers R, Montanari R, Suri N, Uszok A. “Semantic Web Languages for Policy Representation and Reasoning: A Comparison of KAoS, Rei, and Ponder”. International Semantic Web Conference, Florida, USA, 20-23 October 2013.
[22] Lasierra N, Alesanco A, Guillen S, Garcia J. “A Three Stage Ontology-Driven Solution to Provide Personalized Care to Chronic Patients at Home”. Journal of Biomedical Informatics, 46(3), 516-529, 2013.
[23] Ueda M, Takahata M, Nakajima S. “User’s Food Preference Extraction for Personalized Cooking Recipe Recommendation”. 2nd International Workshop on Semantic Personalized Information Management: Retrieval and Recommendation SPIM, Bonn, Germany, 23-24 October 2011.
Pamukkale Univ Muh Bilim Derg, 21(5), 162-171, 2015
Ö. Can, O. Bursa, M. O. Ünalır
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[24] Hella L, Krogstie J. “Personalisation by Semantic Web Technology in Food Shopping”. In Proceedings of the International Conference on Web Intelligence, Mining and Semantics (WIMS’11), Sogndal, Norway, May 25-27, 2011.
[25] Can Ö. Anlamsal Web İçin Kişiselleştirilebilir Ontoloji Tabanlı Erişim Denetimi ve Politika Yönetimi. Doktora Tezi, Ege Üniversitesi, İzmir, Türkiye, 2009.
[26] Can Ö, Sezer E, Bursa O, Ünalır MO. “Personalized Vaccination using Ontology Based Profiling”. 7th Metadata and Semantics Research Conference (MTSR 2013), CCIS 390, Thessaloniki, Greece, 19-22 November 2013.
[27] Snae C, Brückner, M. “FOODS: A Food-Oriented Ontology-Driven System”. 2nd IEEE International Conference on Digital Ecosystems and Technologies (DEST 2008), Phitsanulok, 26-29 February 2008.
[28] Cantais J, Dominguez D. Gigante V, Laera L, Tamma V. “An Example of Food Ontology for Diabetes Control”. Proceedings of the International Semantic Web Conference 2005 Workshop on Ontology Patterns for the Semantic Web”, Galvay, Ireland, 7 November 2005.

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