CFP last date
20 May 2024
Reseach Article

User profile Ontology for the Personalization approach

by Youssouf El Allioui, Omar El Beqqali
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 41 - Number 4
Year of Publication: 2012
Authors: Youssouf El Allioui, Omar El Beqqali
10.5120/5531-7577

Youssouf El Allioui, Omar El Beqqali . User profile Ontology for the Personalization approach. International Journal of Computer Applications. 41, 4 ( March 2012), 31-40. DOI=10.5120/5531-7577

@article{ 10.5120/5531-7577,
author = { Youssouf El Allioui, Omar El Beqqali },
title = { User profile Ontology for the Personalization approach },
journal = { International Journal of Computer Applications },
issue_date = { March 2012 },
volume = { 41 },
number = { 4 },
month = { March },
year = { 2012 },
issn = { 0975-8887 },
pages = { 31-40 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume41/number4/5531-7577/ },
doi = { 10.5120/5531-7577 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:28:46.745980+05:30
%A Youssouf El Allioui
%A Omar El Beqqali
%T User profile Ontology for the Personalization approach
%J International Journal of Computer Applications
%@ 0975-8887
%V 41
%N 4
%P 31-40
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The personalization is to facilitate the expression of the user's need and enable him to obtain relevant information in these information system accesses. The relevance of information is defined by a set of customizable preferences specific to each user or user community. Data describing users are often grouped as profiles. The content of a user's profile varies according to approaches and applications. Existing approaches solves partially problems related to personalization, but it lacks a model giving a complete overview of all aspects of taking into account the preferences of users. In this paper we propose a generic model of profile that includes all aspects of personalization. The proposed model will be the basis of building an ontology called O'Profil able to store all this information, personalize the content and to instantiate the user profile.

References
  1. Budzik J. Hammond K. "Users interactions with everyday applications as context for just-in-time information access". Proceedings of the 5th international conference on intelligent user interfaces, p. 41-51, 2000.
  2. Cranor L. , Dobbs B. , Egelman S. , Hogben G. , Humphrey J. , Langheinrich M. , Marchiori M. , Presler-Marshall M. , Reagle J. , Schunter M. , The Platform for Privacy Preferences 1. 1 (P3P1. 1) Specification. W3C Working Draft 1 July (2005), http://www. w3. org/TR/2005/WD-P3P11-20050701/
  3. Amato G. , Staraccia U. , "User profile modellin and applications to digital libraries", Proceedings of the 3rd European Conference on Research and avanced technology for digital libraries, p. 184-187, 1999.
  4. Bouzeghoub M. , Kostadinov D. , L'art et définition d'un modèle flexible de profils, Actes de la 2ème conférence en personnalisation de l'information : aperçu de l'état de recherche d'informations et applications CORIA'2005, Grenoble, France, 2005
  5. Shearin S. , LiebermanH, Intelligent Profiling by Example, In Proceedings of the 2001 International Conference on Intelligent User Interfaces, Santa Fe, USA, p. 145-151, 2001.
  6. Zemirli N. , Tamine-Lechani L. , Boughanem M. , Présentation et évaluation d'un modèle d'accès personnalisé à l'information basé sur les diagrammes d'influence, Dans les Actes du XXVème congrès INFORSID, Perros-Guirec, France, p. 89-104, 2007.
  7. Koutrika G. , Ioannidis Y. E. , Personalized Queries under a Generalized Preference Model, In Proceedings of the 21st International Conference on Data Engineering (ICDE 2005), Tokyo, Japan, p. 841-852, 2005.
  8. Rocacher D. , Liétard L. , Préférences et quantités dans le cadre de l'interrogation flexible: sur la prise en compte d'expressions quantifiées, Dans les actes des 22e Journées Bases de Données Avancées (BDA), Lille, France, 2006.
  9. Nguyen A. -T. , Denos N. , Berrut C. , Exploitation des données « disponibles à froid » pour améliorer le démarrage à froid dans les systèmes de filtrage d'information, Dans les Actes du XXIVème Congrès INFORSID, Hammamet, Tunisie, p. 81-95, 2006.
  10. Naumann, F. , Freytag J. C. , Spiliopoulou M. , Quality Driven Source Selection Using Data Envelope Analysis, In Proceedings of the MIT Conference on Information Quality (IQ'98), Cambridge, USA, p. 137-152, 1998.
  11. Pretschner A. , Gauch S. , Ontology Based Personalized Search, In Proceedings of the 11th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'99), Chicago, USA, p. 391-398, 1999.
  12. Sieg A. ,Mobasher B. , Lytinen S. , Burke R. , « Using Concept Hierarchies to Enhance User Queries in Web-based Information Retrieval », Arti?cial Intelligence and Applications(AIA), 2004.
  13. Sieg A. , Mobasher B. , Burke R. , Prabu G. , Lytinen S. , « Representing user information context with ontologies », uahci05, 2005.
  14. Challam et al. , 2007 : Challam V. , Gauch S. , Chandramouli A. , « Contextual Search Using Ontology-Based User Pro?les », Proceedings of RIAO 2007, Pittsburgh USA, 30 may - 1 june, 2007.
  15. Liu F. , Yu C. , Meng W. , « Personalized Web Search For Improving Retrieval Effectiveness », IEEE Transactions on Knowledge and Data Engineering, vol. 16, n° 1, p. 28-40, 2004.
  16. Tamine L. , Boughanem M. , Zemirli W. , « Exploiting Multi-Evidence from Multiple User's In terests to Personalizing Information Retrieval », IEEE International Conference on Digital Information Management(ICDIM 2007), 2007a.
  17. Ma Z. , Pant G. , Sheng, « Interest-based personalized search », ACM Transactions on Information Systems, 2007.
  18. Lassila O. , Swick R. , « Resource Description Framework (RDF) Model and Syntax Speci?cation », August, 1998.
  19. Allan et al. , 2002 : Allan J. , al. , « Challenges in information retrieval and langage modelling », Workshop held at the center for intelligent information retrieval, Septembre, 2002.
  20. Saracevic T. , « The strate?ed model of information retrieval interaction : extension and applications », Proceedings of the 60th annual meeting of the American Society for Information Science, Medford, NJ, p. 313-327, 1997.
  21. Fuhr N. , « information retrieval : introduction and survey, post-graduate course on information retrieval, university of Duisburg-Essen, Germany », 2000.
  22. Tamine L. , Calabretto S. , Recherche d'information contextuelle et Web, Ouvrage intitulé recherche d'information sur le web, édition hermes, à paraître, IRIT, France, 2007b.
  23. Miller B. , Konstan J. , Matlz D. , Herlocker J. , Gordan L. , Riedl A. , « GroupLens : applying collaborative ?ltering Usenet news, Communications of ACM », March, 1997.
  24. Lieberman H. , « Autonomous interface agents », ACM Conference on Human-Computer Interface, p. 67-74, March, 1997.
  25. Dimitre Kostadinov, Thèse : Personnalisation de l'information : une approche de gestion de profils et de reformulation de requêtes. Version 1 - 22 Sep 2008, UNIVERSITE DE VERSAILLES SAINT-QUENTIN-EN-YVELINES
  26. Noy NF, McGuinness DL. Ontology development 101: a guide to creating your first ontology; 2001. Report No. : Stanford Knowledge Systems Laboratory Technical Report KSL-01-05, Stanford Medical Informatics Technical Report SMI-2001-0880.
  27. Smith B, Ceusters W, Klagges B, Kohler J, Kumar A, Lomax J, et al. Relations in biomedical ontologies. Genome Biol 2005;6(5):R46.
  28. El Allioui Y. , El Beqqali O. : O'Neurolog - Building an Ontology for Neurology in Mobile Environment. IJCSNS - International Journal of Computer Science and Network Security, 2010. Vol. 10 No. 9 pp. 188-197.
  29. E. Sirin, B. Parsia, B. Grau, A. Kalyanpur, Y. Katz. Pellet: A practical OWL-DL reasoner. Web Semantics: Science, Services and Agents on the World Wide Web In Software Engineering and the Semantic Web, Vol. 5, No. 2. (June 2007), pp. 51-53. doi:10. 1016/j. websem. 2007. 03. 004 Key: citeulike:2615678.
Index Terms

Computer Science
Information Sciences

Keywords

Personalization Ontology User Profile Context Preference Profile Model