We engineer an algorithm to solve the approximate dictionary matching problem. Given a list of words W, maximum distance d fixed at preprocessing time and a query word q, we would like to retrieve all words from W that can be transformed into q with d or less edit operations. We present data structures that support fault tolerant queries by generating an index. On top of that, we present a generalization of the method that eases memory consumption and preprocessing time significantly. At the same time, running times of queries are virtually unaffected. We are able to match in lists of hundreds of thousands of words and beyond within microseconds for reasonable distances. © 2010 Springer-Verlag.
CITATION STYLE
Karch, D., Luxen, D., & Sanders, P. (2010). Improved fast similarity search in dictionaries. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6393 LNCS, pp. 173–178). https://doi.org/10.1007/978-3-642-16321-0_16
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