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Issue No.04 - July/August (2009 vol.11)
pp: 6-9
Fedor Bakalov , University of Jena
Birgitta König-Ries , University of Jena
Andreas Nauerz , IBM Deutschland Research and Development Germany GmbH
Martin Welsch , IBM Deutschland Research and Development Germany GmbH
The increasing number of resources available through portals establish a need to tailor information to individual needs and situations. Mashups are tools for dynamically integrating independent applications. For portals, what is needed are means to automatically create personalized mashups that optimally fit a user's information needs in a given situation. At the core of our approach are different ontology-based models that describe the user, the domain, possible information needs in this domain, and personalization rules determining which information to present to which user in which situation.
Internet/Web, software engineering, mashups, Web portals, ontologies
Fedor Bakalov, Birgitta König-Ries, Andreas Nauerz, Martin Welsch, "Automating Mashups for Next-Generation Enterprise Portals", IT Professional, vol.11, no. 4, pp. 6-9, July/August 2009, doi:10.1109/MITP.2009.68
1. F. Balakov et al., "Ontology-Based Multidimensional Personalization Modeling for the Automatic Generation of Mashups in Next-Generation Portals," Proc. 2008 1st Int'l Workshop Ontologies in Interactive Systems (Ontoract 08), IEEE CS Press, 2008, pp. 75–82.
2. B. Crabtree and S.J. Soltysiak, "Identifying and Tracking Changing Interests," Int'l J. Digital Libraries, vol. 2, no. 1, 1998, pp. 38–53.
3. P. Achananuparp et al., "Semantically Enhanced User Modeling," Proc. 2007 ACM Symp. Applied Computing (SAC 07), ACM Press, 2007, pp. 1335–1339.
4. A. Schmidt, "Enabling Learning on Demand in Semantic Work Environments: The Learning in Process Approach," Emerging Technologies for Semantic Work Environments: Techniques, Methods, and Applications, IGI Publishing, 2008.
5. H. Zhang, Y. Song, and H.-T. Song, "Construction of Ontology-Based User Model for Web Personalization," User Modeling, LNCS 4511, Springer, 2007, pp. 67–76.
6. C.D.C. Pereira and A. Tettamanzi, "An Evolutionary Approach to Ontology-Based User Model Acquisition, Fuzzy Logic and Applications, LNCS 2955, Springer, 2003, pp. 25–32.
7. A. Kavcic, "Fuzzy User Modeling for Adaptation in Educational Hypermedia," IEEE Trans. Systems, Man, and Cybernetics, Part C: Applications and Reviews, vol. 34, no. 4, 2004, pp. 439–449.
8. R.I. John and G.J. Mooney, "Fuzzy User Modeling for Information Retrieval on the World Wide Web," Knowledge and Information Systems, vol. 3, no. 1, 2001, pp. 81–95.
9. G.B. Lamont and D.A.V. Veldhuizen, Evolutionary Algorithms for Solving Multi-Objective Problems, Kluwer Academic Publishers, 2002.
10. T. Fischer, F. Bakalov, and A. Nauerz, Towards an Automatic Service Composition for Generation of User-Sensitive Mashups, tech. report 448, Dept. Computer Science, Univ. of Würzburg, 2008, pp. 14–16.
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