Abstract
Our work addresses the problem of information retrieval (IR) in an heterogeneous environment by a model driven information retrieval infrastructure that allows each user to explicitly personalize the indexing and retrieval processes. In this paper, we propose an ontological approach to represent a particular user’s need, his preferences, his context and his processes within the information system. Then, we define an algorithm to automatically construct personalized IR models. Afterwards, we describe an architecture to handle these models in order to provide personalized answers. Lastly, we show that system responses are entirely personalized and semantically enhanced by the ontological representation behind. These contributions are designed to allow the integration of external knowledge and their fundations enable an adaptation to various applications.
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References
Abiteboul, S., Manolescu, I., Rigaux, P., Rousset, M.C., Senellart, P.: Web Data Management. Cambridge University Press (2011)
Beppler, F.D., Fonseca, F.T., Pacheco, R.C.S.: Hermeneus: An Architecture for an Ontology-Enabled Information Retrieval (2008)
Bruno, E., Faessel, N., Glotin, H., Le Maitre, J., Scholl, M.: Indexing and querying segmented web pages: the blockweb model. World Wide Web 14(5), 623–649 (2011), doi:10.1007/s11280-011-0124-6
Deerwester, S., Dumais, S.T., Furnas, G.W., Landauer, T.K., Harshman, R.: Indexing by latent semantic analysis. Journal of the American Society for Information Science 41, 391–407 (1990)
Fernández, M., Cantador, I., Lopez, V., Vallet, D., Castells, P., Motta, E.: Semantically enhanced information retrieval: An ontology-based approach. J. Web Sem. 9(4), 434–452 (2011)
W3C OWL Working Group. OWL Web Ontology Language: Overview, W3C Recommendation (2009)
Gruber, T.R.: Towards principles for the design of ontologies used for knowledge sharing in formal ontology in conceptual analysis and knowledge representation. Kluwer Academic Publishers (1993)
Manning, C.D., Raghavan, P., Schtze, H.: Introduction to Information Retrieval. Cambridge University Press, New York (2008)
Maron, M.E., Kuhns, J.L.: On relevance, probabilistic indexing and information retrieval. J. ACM 7, 216–244 (1960)
Mylonas, P., Vallet, D., Castells, P., Fernández, M., Avrithis, Y.: Personalized information retrieval based on context and ontological knowledge. Knowledge Engineering Review 23(1) (2008)
Ponte, J.M., Croft, W.B.: A language modeling approach to information retrieval. In: SIGIR 1998: Proceedings of the 21st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 275–281. ACM Press, New York (1998)
Robertson, S.E., Walker, S., Jones, S., Hancock-Beaulieu, M.M., Gatford, M.: Okapi at trec-3, pp. 109–126 (1996)
Salton, G., Wong, A., Yang, C.S.: A vector space model for automatic indexing. Commun. ACM 18, 613–620 (1975)
Singhal, A., Buckley, C., Mitra, M., Mitra, A.: Pivoted document length normalization, pp. 21–29. ACM Press (1996)
Turtle, H., Croft, W.B.: Inference networks for document retrieval. In: Proceedings of the 13th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 1990, pp. 1–24. ACM, New York (1990)
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Martin, V., Bruno, E., Murisasco, E. (2014). Ontology Driven Indexing: Application to Personalized Information Retrieval. In: Decker, H., Lhotská, L., Link, S., Spies, M., Wagner, R.R. (eds) Database and Expert Systems Applications. DEXA 2014. Lecture Notes in Computer Science, vol 8644. Springer, Cham. https://doi.org/10.1007/978-3-319-10073-9_19
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DOI: https://doi.org/10.1007/978-3-319-10073-9_19
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