Abstract
The use of knowledge in the information retrieval process allows the return of documents semantically related to the initial user’s query. This knowledge can be encoded in a knowledge base to be used in information retrieval systems. The framework for information retrieval based on fuzzy relations and multiple ontologies is a proposal to retrieve information using a knowledge base composed of multiple related ontologies whose relationships are expressed as fuzzy relations. Using this knowledge organization a new method to expand the user query is proposed. The framework provides a way that each ontology can be represented independently as well as their relationships. The proposed framework performance is compared with another fuzzy-based approach for information retrieval. Also the query expansion method is tested with the Apache Lucene search engine. In both cases the proposed framework improves the obtained results.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Baeza-Yates, R.A., Ribeiro-Neto, B.A.: Modern Information Retrieval. ACM Press / Addison-Wesley, New York (1999)
Ogawa, Y., Morita, T., Kobayashi, K.: A fuzzy document retrieval system using the keyword connection matrix and a learning method. In: Fuzzy Sets and Systems, vol. 39, pp. 163–179. Elsevier B. V, Amsterdam (1991)
Widyantoro, D.H., Yen, J.: A fuzzy ontology-based abstract search engine and its user studies. In: 10th IEEE International Conference on Fuzzy Systems, pp. 1291–1294. IEEE Computer Society, Washington (2001)
Bhogal, J., Macfarlane, A., Smith, P.: A review of ontology based query expansion. In: Information Processing and Management, vol. 43, pp. 866–886. Elsevier B. V, Amsterdam (2007)
Abulaish, M., Dey, L.: A fuzzy ontology generation framework for handling uncertainties and nonuniformity in domain knowledge description. In: International Conference on Computing: Theory and Applications, pp. 287–293. IEEE Computer Society, Washington (2007)
Lau, R.Y.K., Li, Y., Xu, Y.: Mining fuzzy domain ontology from textual databases. In: IEEE/WIC/ACM International Conference on Web Intelligence, pp. 156–162. IEEE Computer Society, Washington (2007)
Parry, D.: A fuzzy ontology for medical document retrieval. In: Second Workshop on Australasian Information Security, Data Mining and Web Intelligence, and Software Internationalisation, pp. 121–126. Australian Computer Society Inc., Darlinghurst (2004)
Gomez-Pérez, A., Fernández-Lopez, M., Corcho, O.: Ontological Engineering. Springer, London (2003)
Chen, S.M., Horng, Y.J., Lee, C.H.: Fuzzy information retrieval based on multi-relationship fuzzy concept networks. In: Fuzzy Sets and Systems, vol. 140, pp. 183–205. Elsevier B. V, Amsterdam (2003)
Horng, Y.J., Chen, S.M., Lee, C.H.: Automatically constructing multi-relationship fuzzy concept networks for document retrieval. In: Applied Artificial Intelligence, vol. 17, pp. 303–328. Taylor & Francis, Philadelphia (2003)
Apache lucene overview, http://lucene.apache.org/java/docs/index.html
Bratsas, C., Koutkias, V., Kaimakamis, E., Bamidis, P., Maglaveras, N.: Ontology-based vector space model and fuzzy query expansion to retrieve knowledge on medical computational problem solutions. In: 29th IEEE Annual International Conference on Engineering in Medicine and Biology Society, pp. 3794–3797. IEEE Computer Society, Washington (2007)
Pereira, R., Ricarte, I., Gomide, F.: Fuzzy relational ontological model in information search systems. In: Sanchez, E. (ed.) Fuzzy Logic and The Semantic Web, pp. 395–412. Elsevier B. V, Amsterdam (2006)
Pedrycz, W., Gomide, F.: An introduction to fuzzy sets: Analysis and Design. MIT Press, Cambridge (1998)
Sisga - Ensino Mapa do Clima no Brasil, http://campeche.inf.furb.br/sisga/educacao/ensino/mapaClima.php
Köppen, http://en.wikipedia.org/wiki/Koppen_climate_classification
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Leite, M.A.A., Ricarte, I.L.M. (2008). A Framework for Information Retrieval Based on Fuzzy Relations and Multiple Ontologies. In: Geffner, H., Prada, R., Machado Alexandre, I., David, N. (eds) Advances in Artificial Intelligence – IBERAMIA 2008. IBERAMIA 2008. Lecture Notes in Computer Science(), vol 5290. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88309-8_30
Download citation
DOI: https://doi.org/10.1007/978-3-540-88309-8_30
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-88308-1
Online ISBN: 978-3-540-88309-8
eBook Packages: Computer ScienceComputer Science (R0)