Abstract
This paper introduces an indexing technique for fuzzy numerical data which relies on the classical, well-known and well-spread B+tree index data structure. The proposed indexing technique is specifically devised to increase the performance of query processing when a possibility measured flexible condition is involved. The proposal relies on the use of an indexing data structure implemented in virtually every database management system. This feature makes the proposal a good candidate to be used, with very low implementation effort, in a fuzzy database management system created as an extension of a classical one. The paper includes a performance analysis of the proposed indexing technique in contrast with other purpose equivalent techniques in order to evaluate the suitability of the proposal.
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Barranco, C.D., Campaña, J.R., Medina, J.M. (2007). An Indexing Technique for Fuzzy Numerical Data. In: Prade, H., Subrahmanian, V.S. (eds) Scalable Uncertainty Management. SUM 2007. Lecture Notes in Computer Science(), vol 4772. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75410-7_14
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DOI: https://doi.org/10.1007/978-3-540-75410-7_14
Publisher Name: Springer, Berlin, Heidelberg
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