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An Adaptive Navigation Method for Semi-structured Data

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Advances in Databases and Information Systems

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 186))

Abstract

The navigation adaptation is the solution that supports the user during his interaction with the system. In the literature, several works that deal with the navigation adaptation are proposed. They guide the user from a document to another, provide the user with a set of links leading to the pertinent documents, or apply on simple links the suitable adaptive navigation technologies. In this paper, we contribute to propose a method that identifies the best navigation path between semi-structured result documents according to the user’s needs, history and device.

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References

  1. Armstrong, R., Freitag, D., Joachims, T., Mitchell, T.: WebWatcher: A learning apprentice for the World Wide Web. In: Proceeding Of AAAI Spring Symposium on Information Gathering from Distributed, Heterogeneous Environments, pp. 6–12. AAAI Press (1995)

    Google Scholar 

  2. Brusilovsky, P.: Methods and techniques of adaptive hypermedia. In: User Modeling and User-Adapted Interaction, pp. 87–129 (1996)

    Google Scholar 

  3. Chiou, C.-K., Tseng, J.C.R., Hwang, G.-J., Heller, S.: An adaptive navigation support system for conducting context-aware ubiquitous learning in museums. Journal: Computers and Education (2010)

    Google Scholar 

  4. De Bra, P., Aerts, A., Berden, B., de Lange, B., Rousseau, B., Santic, T., Smits, D., Stash, N.: AHA! The Adaptive Hypermedia Architecture. In: Proceedings of the ACM Hypertext Conference (2003)

    Google Scholar 

  5. Doerr, C., Dincklage, D.V., Diwan, A.: Simplifying Web Traversals By Recognizing Behavior Patterns. In: HT 2007: Proceedings of the 18th Conference on Hypertext and Hypermedia, pp. 105–114 (2007)

    Google Scholar 

  6. Hohl, H., Böcker, H.-D., Gunzenhäuser, R.: Hypadapter: An adaptive hypertext system for exploratory learning and programming. In: User Modeling and User-Adapted Interaction, vol. 6, pp. 131–156 (1996)

    Google Scholar 

  7. Knutov, E.: GAF: Generic Adaptation Framework. In: Nejdl, W., Kay, J., Pu, P., Herder, E. (eds.) AH 2008. LNCS, vol. 5149, pp. 400–404. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  8. Lassila, O.: Web Metadata: A matter of Semantics. IEEE on Internet Computing 2(4), 30–37 (1998)

    Article  Google Scholar 

  9. Seo, J., Diaz, F., Gabrilovich, E., Josifovski, V., Pang, B.: Generalized Link Suggestions via Web Site Clustering. In: WWW 2011: Proceedings of the 20th International Conference on World Wide Web (2011)

    Google Scholar 

  10. Verma, S., Patel, S., Abhari, A.: Adaptive web navigation. In: SpringSim 2009 Proceedings of the 2009 Spring Simulation Multiconference (2009)

    Google Scholar 

  11. Weber, G., Brusilovsky, P.: ELM-ART: An adaptive versatile system for Web based instruction. International Journal of Artificial Intelligence in Education 12(4), 351–384 (2001)

    Google Scholar 

  12. Wanga, Y.-T., Lee, A.J.T.: Mining Web navigation patterns with a path traversal graph. Expert Systems with Applications 38, 7112–7122 (2011)

    Article  Google Scholar 

  13. Zayani, C.: Towards an Adaptation of Semi-structured Document Querying. In: CIR 2007 (2007)

    Google Scholar 

  14. Zghal Rebai, R., Zayani, C., Amous, I.: MEDI-ADAPT: A distributed architecture for personalized access to heteroneneous semi-structured data. In: WEBIST, pp. 259–263 (2012)

    Google Scholar 

  15. Zhu, T., Greiner, R., Haeubl, G.: Learning a model of a web user’s interests. In: 9th International Conference on User Modeling (2003)

    Google Scholar 

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Correspondence to Rim Zghal Rebai .

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Zghal Rebai, R., Zayani, C.A., Amous, I. (2013). An Adaptive Navigation Method for Semi-structured Data. In: Morzy, T., Härder, T., Wrembel, R. (eds) Advances in Databases and Information Systems. Advances in Intelligent Systems and Computing, vol 186. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32741-4_19

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  • DOI: https://doi.org/10.1007/978-3-642-32741-4_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32740-7

  • Online ISBN: 978-3-642-32741-4

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