Abstract
The paper proposed an intelligent Personalized E-Learning System as a way to make the E-learning more personalized. Portal technology serves an essential role to the development of the personalized learning, and offers convenient tools for users. Although most E-learning system offer complete learning information, they simply offer functions of view and search and do not provide a personalized learning environment. This study aims to develop a Personalized E-Learning System Based on Portal Technology that unlike the traditional E-learning system use a number of intelligent methods, including information extraction, information retrieval, and some heuristic algorithm and provide more meaningful and personalized information to users.
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References
Ed Lightfoot and Weldon Ihrig. The Next-Generation Infrastructure. EDUCAUSE Review (November 2002)
Buttler, D., Liu, L., Pu, C.: A Fully Automated Object Extraction System for the World Wide Web. In: 21st International Conference on Distributed Computing Systems, pp. 361–370 (April 2001)
Chang, C.-H., Liu, S.-C., Wu, Y.-C.: Applying pattern mining to Web information extraction. In: 5th Pacific Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2000), pp. 4–6 (April 2001)
Baeze-Yates, R., Ribeiro-Neto, B.A.: And Artificial System. MIT Press, Boston (1922)
Moffat, A., Zobel, J.: Compression and Fast Indexing for Multi-Gigabit Text Databases. Australian Compute 26(1), 19 (1994)
Hao, X.W., Ma, J.: A platform for distance education. In: The 3th Asia and Pacific Conference on Web Computing, pp. 117–123. Xian Kluwer Academic Publisher, Dordrecht (2000)
Tsai, C.-W., Ho, J.-H., Liang, T.-W., Yang, C.-S.: An intelligent Web portal system for Web information region integration, pp. 3878–3883 (October 2005)
Adomavicius, G., Tuzhilin, A.: User profiling in personalization applications through rule discovery and validation. In: Proceeding of the 5th International Conference on Data Mining and Knowledge Discovery, pp. 377–381 (1999)
Guarino, N.: Formal Ontology and Information System. In: Proc. of FIOS 1998 Formal Ontology in Information Systems,Trento, Italy (June 1998)
Christ, M., Krishnan, R., Nagin, D., Gunther, O.: Measuring Web portal utilization. In: Proceedings of the 35th Annual Hawaii International Conference System Sciences, HICSS, pp. 2647–2653 (2002)
Guarion Semantic Matching:Formal Ontological Distinctions for Information Organization,Extraction and Integration. In: Pazienza, M.T. (ed.) SCIE 1997. LNCS, vol. 1299, pp. 139–170. Springer, Heidelberg (1997)
Wu, Y.-H., Chen, Y.-C., Chen, A.L.P.: Enabling personalized recommendation on the Web based on user interests and behaviors. In: Proceedings. Eleventh International Workshop Research Issues in Data Engineering, pp. 17–24 (2001)
Kotsakis, E., Bohm, K.: XML Schema Directory: a data structure for XML data processing. Web Information Systems Engineering (2000); Smith, T.F., Waterman, M.S.: Identification of Common Molecular Subsequences. J. Mol. Biol. 147, 195–197 (1981)
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Cui, X., Zhang, S. (2011). The Personalized E-Learning System Based on Portal Technology. In: Zhiguo, G., Luo, X., Chen, J., Wang, F.L., Lei, J. (eds) Emerging Research in Web Information Systems and Mining. WISM 2011. Communications in Computer and Information Science, vol 238. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24273-1_59
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DOI: https://doi.org/10.1007/978-3-642-24273-1_59
Publisher Name: Springer, Berlin, Heidelberg
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