Abstract
Case Retrieval Networks (CRNs) facilitate flexible and efficient retrieval in Case-Based Reasoning (CBR) systems. While CRNs scale up well to handle large numbers of cases in the case-base, the retrieval efficiency is still critically determined by the number of feature values (referred to as Information Entities) and by the nature of similarity relations defined over the feature space. In textual domains it is typical to perform retrieval over large vocabularies with many similarity interconnections between words. This can have adverse effects on retrieval efficiency for CRNs. This paper proposes an extension to CRN, called the Fast Case Retrieval Network (FCRN) that eliminates redundant computations at run time. Using artificial and real-world datasets, it is demonstrated that FCRNs can achieve significant retrieval speedups over CRNs, while maintaining retrieval effectiveness.
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
Lenz, M., Burkhard, H.-D.: Case Retrieval Nets: Basic Ideas and Extensions. KI, 227–239 (1996)
Chakraborti, S., Ambati, S., Balaraman, V., Khemani, D.: Integrating Knowledge Sources and Acquiring Vocabulary for Textual CBR. In: Proc. of the 8th UK CBR Workshop, pp. 74–84 (2003)
Lenz, M., Burkhard, H.: Case Retrieval Nets: Foundations, Properties, Implementation, and Results, Technical Report, Humboldt-Universität zu, Berlin (1996)
Lenz, M.: Knowledge Sources for Textual CBR Applications, Textual CBR: Papers from the 1998 Workshop Technical Report WS-98-12, pp. 24–29. AAAI Press (1998)
Balaraman, V., Chakraborti, S.: Satisfying Varying Retrieval Requirements in Case-Based Intelligent Directory Assistance. In: Proc. of the FLAIRS Conference (2004)
Lenz, M.: Case Retrieval Nets Applied to Large Case-Bases. In: Proc. 4th German Workshop on CBR, Informatik Preprints, Humboldt-Universität zu, Berlin (1996)
Lenz, M., Auriol, E., Manago, M.: Diagnosis and Decision Support. In: Lenz, M., Bartsch-Spörl, B., Burkhard, H.-D., Wess, S. (eds.) Case-Based Reasoning Technology. LNCS, vol. 1400, pp. 51–90. Springer, Heidelberg (1998)
Rijsbergen, C.J.: Information Retrieval, 2nd edn. Butterworths, London (1979)
Delany, S.J., Cunningham, P., Tsymbal, A., Coyle, L.: A Case-based Technique for Tracking Concept Drift in Spam Filtering. In: Webb, G.I., Yu, X. (eds.) AI 2004. LNCS (LNAI), vol. 3339, pp. 3–16. Springer, Heidelberg (2004)
Lenz, M., Burkhard, H.-D.: CBR for Document Retrieval - The FAllQ Project. In: Leake, D.B., Plaza, E. (eds.) ICCBR 1997. LNCS, vol. 1266. Springer, Heidelberg (1997)
Chakraborti, S., Watt, S., Wiratunga, N.: Introspective Knowledge Acquisition in Case Retrieval Networks for Textual CBR. In: Proc. of the 9th UK CBR Workshop, pp. 51–61 (2004)
Wilson, D., Bradshaw, S.: CBR Textuality. In: Proc. of the Fourth UK Case-Based Reasoning Workshop, pp. 67–80 (1999)
Lytinen, S.L., Tomuro, N.: The Use of Question Types to Match Questions in FAQFinder, Mining Answers From Texts and Knowledge Bases, AAAI Technical Report SS-02-06, pp. 46–53. AAAI Press (2002)
Lenz, M.: Case Retrieval Nets as a Model for Building Flexible Information Systems, Ph.D dissertation, Humboldt Uni. Berlin. Faculty of Mathematics and Natural Sciences (1999)
Lenz, M., Hubner, A., Kunje, M.: Textual CBR. In: Lenz, M., Bartsch-Spörl, B., Burkhard, H.-D., Wess, S. (eds.) Case-Based Reasoning Technology. LNCS (LNAI), vol. 1400, pp. 115–137. Springer, Heidelberg (1998)
Yang, Y., Pederson, J.O.: A Comparative Study on Feature Selection in Text Categorization. In: Proc. of the International Conference on Machine Learning, pp. 412–420 (1997)
Kolodner, J.L.: Case-Based Reasoning. Morgan Kaufmann, San Mateo (1993)
Schaaf, J.W.: “Fish and Sink”: An Anytime Algorithm to Retrieve Adequate Cases. In: Aamodt, A., Veloso, M.M. (eds.) ICCBR 1995. LNCS, vol. 1010, pp. 371–380. Springer, Heidelberg (1995)
Weβ, S., Althoff, K.-D., Derwand, G.: Using k-d trees to Improve the Retrieval Step in Case-Based Reasoning. In: Wess, S., Richter, M., Althoff, K.-D. (eds.) EWCBR 1993. LNCS, vol. 837, pp. 167–181. Springer, Heidelberg (1994)
Rumelhart, D.E., McClelland, J.L.: PDP Research Group. In: Parallel distributed Processing: Explorations in the Microstructure of Cognition. Foundations, vol. 1. MIT Press, Cambridge (1986)
Wolverton, M.: An Investigation of Marker Passing Algorithms for Analogue Retrieval. In: Aamodt, A., Veloso, M.M. (eds.) ICCBR 1995. LNCS, vol. 1010, pp. 359–370. Springer, Heidelberg (1995)
Wolverton, M., Hayes-Roth, B.: Retrieving Semantically Distant Analogies with Knowledge-Directed Spreading Activation. In: Proc. AAAI 1994 (1994)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Chakraborti, S., Lothian, R., Wiratunga, N., Orecchioni, A., Watt, S. (2006). Fast Case Retrieval Nets for Textual Data. In: Roth-Berghofer, T.R., Göker, M.H., Güvenir, H.A. (eds) Advances in Case-Based Reasoning. ECCBR 2006. Lecture Notes in Computer Science(), vol 4106. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11805816_30
Download citation
DOI: https://doi.org/10.1007/11805816_30
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-36843-4
Online ISBN: 978-3-540-36846-5
eBook Packages: Computer ScienceComputer Science (R0)