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Improved Fast Similarity Search in Dictionaries

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String Processing and Information Retrieval (SPIRE 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6393))

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Abstract

We engineer an algorithm to solve the approximate dictionary matching problem. Given a list of words \(\mathcal{W}\), maximum distance d fixed at preprocessing time and a query word q, we would like to retrieve all words from \(\mathcal{W}\) 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.

Partially supported by DFG Grant 933/5-1. A full version of the paper is available at http://arxiv.org/abs/1008.1191 . We would like to thank Johannes Fischer for the fruitful discussions and the anonymous referees for the detailed reviews.

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Karch, D., Luxen, D., Sanders, P. (2010). Improved Fast Similarity Search in Dictionaries. In: Chavez, E., Lonardi, S. (eds) String Processing and Information Retrieval. SPIRE 2010. Lecture Notes in Computer Science, vol 6393. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16321-0_16

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  • DOI: https://doi.org/10.1007/978-3-642-16321-0_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16320-3

  • Online ISBN: 978-3-642-16321-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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