Abstract
One of the important issues in information retrieval is to provide methods suitable for searching in large textual datasets. Some improvement of the retrieval process can be achieved by usage of conceptual models created automatically for analysed documents. One of the possibilities for creation of such models is to use well-established theory and methods from the area of Formal Concept Analysis. In this work we propose conceptual models based on the generalized one-sided concept lattices, which are locally created for subsets of documents represented by object-attribute table (document-term table in case of vector representation of text documents). Consequently, these local concept lattices are combined to one merged model using agglomerative clustering algorithm based on the descriptive (keyword-based) representation of particular lattices. Finally, we define basic details and methods of IR system that combines standard full-text search and conceptual search based on the extracted conceptual model.
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
Ben Yahia, S., Jaoua, A.: Discovering knowledge from fuzzy concept lattice. In: Kandel, A., Last, M., Bunke, H. (eds.) Data Mining and Computational Intelligence, pp. 167–190. Physica-Verlag, Heidelberg (2001)
Butka, P.: Combination of problem reduction techniques and fuzzy FCA approach for building of conceptual models from textual documents. In: Paralic, J., Dvorsky, J., Kratky, M. (eds.) ZNALOSTI 2006, Proceedings of the 5th Annual Conference, Ostrava, Czech Republic, pp. 71–82 (2006)
Butka, P., Pocs, J.: Generalization of one-sided concept lattices (2011) (Submitted)
Butka, P., Pocsova, J.: Hierarchical FCA-based conceptual model of text documents used in information retrieval system. In: Proceedings of 6th IEEE International Symposium on Applied Computational Intelligence and Informatics (SACI 2011), Timisoara, Romania, pp. 199–204 (2011)
Butka, P., Sarnovsky, M., Bednar, P.: One Approach to Combination of FCA-based Local Conceptual Models for Text Analysis – Grid-based approach. In: Proceedings of 6th International Symposium on Applied Machine Intelligence (SAMI 2008), Herlany, Slovakia, pp. 131–135 (2008)
Dittenbach, M., Merkl, D., Rauber, A.: Using growing hierarchical self-organizing maps for document classification. In: Proceedings of European Symposium on Artificial Neural Networks (ESANN 2000), Bruges, Belgium, pp. 7–12 (2000)
Ganter, B., Wille, R.: Formal Concept Analysis. Springer, Berlin (1997)
Krajci, S.: Cluster based efficient generation of fuzzy concepts. Neural Netw. World 13, 521–530 (2003)
Ore, O.: Galois Connexions. Trans. Am. Math. Soc. 55, 493–513 (1944)
Quan, T.T., Hui, S.C., Cao, T.H.: A Fuzzy FCA-based Approach to Conceptual Clustering for Automatic Generation of Concept Hierarchy on Uncertainty Data. In: Proceedings of CLA conference (CLA 2004), Ostrava, Czech Republic, pp. 1–12 (2004)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag GmbH Berlin Heidelberg
About this chapter
Cite this chapter
Butka, P., Pócsová, J., Pócs, J. (2012). A Proposal of the Information Retrieval System Based on the Generalized One-Sided Concept Lattices. In: Precup, RE., Kovács, S., Preitl, S., Petriu, E. (eds) Applied Computational Intelligence in Engineering and Information Technology. Topics in Intelligent Engineering and Informatics, vol 1. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28305-5_5
Download citation
DOI: https://doi.org/10.1007/978-3-642-28305-5_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-28304-8
Online ISBN: 978-3-642-28305-5
eBook Packages: EngineeringEngineering (R0)