Results 11 to 20 of about 34,882 (289)
CoRRWe define and investigate the Fréchet edit distance problem. Given two polygonal curves $π$ and $σ$ and a threshhold value $δ>0$, we seek the minimum number of edits to $σ$ such that the Fréchet distance between the edited $σ$ and $π$ is at most $δ$. For the edit operations we consider three cases, namely, deletion of vertices, insertion of vertices,
Emily Fox +3 more
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Secure approximation of edit distance on genomic data [PDF]
BMC Medical Genomics, 2017 Background Edit distance is a well established metric to quantify how dissimilar two strings are by counting the minimum number of operations required to transform one string into the other.
Md Momin Al Aziz +2 more
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A contextual normalised edit distance [PDF]
2008 IEEE 24th International Conference on Data Engineering Workshop, 2008 In order to better fit a variety of pattern recognition problems over strings, using a normalised version of the edit or Levenshtein distance is considered to be an appropriate approach. The goal of normalisation is to take into account the lengths of the strings.
Colin de la Higuera, Luisa Micó
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Approximating the edit distance for genomes with duplicate genes under DCJ, insertion and deletion [PDF]
BMC Bioinformatics, 2012 Computing the edit distance between two genomes under certain operations is a basic problem in the study of genome evolution. The double-cut-and-join (DCJ) model has formed the basis for most algorithmic research on rearrangements over the last few years.
Shao Mingfu, Lin Yu
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Approximating Edit Distance Efficiently [PDF]
45th Annual IEEE Symposium on Foundations of Computer Science, 2004 Edit distance has been extensively studied for the past several years. Nevertheless, no linear-time algorithm is known to compute the edit distance between two strings, or even to approximate it to within a modest factor. Furthermore, for various natural algorithmic problems such as low-distortion embeddings into normed spaces, approximate nearest ...
Ziv Bar-Yossef +3 more
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2018 24th International Conference on Pattern Recognition (ICPR), 2018 In this paper, we present a novel distance metric called Segmentation Edit Distance (SED) and its use as a segmentation evaluation metric. In segmentation evaluation, the difference or distance of a test segmentation and the associated ground truth segmentation are measured in order to compare different algorithms.
Daniel Pucher, Walter G. Kropatsch
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Proceedings of the Sixth Workshop on Structured Prediction for NLP, 2022 We propose the neural string edit distance model for string-pair matching and string transduction based on learnable string edit distance. We modify the original expectation-maximization learned edit distance algorithm into a differentiable loss function, allowing us to integrate it into a neural network providing a contextual representation of the ...
Libovický, Jindřich, Fraser, Alexander
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Kendall tau sequence distance: Extending Kendall tau from ranks to sequences [PDF]
EAI Endorsed Transactions on Industrial Networks and Intelligent Systems, 2020 An edit distance is a measure of the minimum cost sequence of edit operations to transform one structureinto another. Edit distance can be used as a measure of similarity as part of a pattern recognition system, withlower values of edit distance implying
Vincent Cicirello
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Privacy-preserving Hamming and Edit Distance Computation and Applications [PDF]
Jisuanji kexue, 2022 With the rapid development of information technology,privacy-preserving multiparty cooperative computation is becoming more and more popular.Secure multiparty computation is a key technology to address such problems.In scientific research and practical ...
DOU Jia-wei
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Toward Efficient Similarity Search under Edit Distance on Hybrid Architectures
Information, 2022 Edit distance is the most widely used method to quantify similarity between two strings. We investigate the problem of similarity search under edit distance.
Madiha Khalid +2 more
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