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Approximate Point Set Pattern Matching with L p -Norm

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String Processing and Information Retrieval (SPIRE 2011)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7024))

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Abstract

Given two sets of points, the text and the pattern, determining whether the pattern “appears” in the text is modeled as the point set pattern matching problem. Applications usually ask for not only exact matches between these two sets, but also approximate matches. In this paper, we investigate a one-dimensional approximate point set matching problem proposed in [T. Suga and S. Shimozono, Approximate point set pattern matching on sequences and planes, CPM’04]. What requested is an optimal match which minimizes the L p -norm of the difference vector (|p 2 − p 1 − (t2 − t1)|, |p 3 − p 2 − (t3 − t2)|, …, |p m  − p m − 1 − (t m  − t m − 1)|), where p 1, p 2, …, p m is the pattern and t1, t2, …, t m is a subsequence of the text. For p → ∞, the proposed algorithm is of time complexity O(mn), where m and n denote the lengths of the pattern and the text, respectively. For arbitrary p < ∞, the time complexity is O(mnT(p)), where T(p) is the time of evaluating x p for x ∈ R.

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Wang, HL., Chen, KY. (2011). Approximate Point Set Pattern Matching with L p -Norm. In: Grossi, R., Sebastiani, F., Silvestri, F. (eds) String Processing and Information Retrieval. SPIRE 2011. Lecture Notes in Computer Science, vol 7024. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24583-1_9

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  • DOI: https://doi.org/10.1007/978-3-642-24583-1_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24582-4

  • Online ISBN: 978-3-642-24583-1

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