Evaluate the performance of K-means distance functions with string edit distance and the open directory project

Learning string-edit distance

IEEE Transactions on Pattern Analysis and Machine Intelligence ◽

10.1109/34.682181 ◽

1998 ◽

Vol 20 (5) ◽

pp. 522-532 ◽

Cited By ~ 348

Author(s):

E.S. Ristad ◽

P.N. Yianilos

Keyword(s):

Edit Distance ◽

String Edit Distance

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Sketch-Based User Authentication With a Novel String Edit Distance Model

IEEE Transactions on Systems Man and Cybernetics Systems ◽

10.1109/tsmc.2016.2601074 ◽

2018 ◽

Vol 48 (3) ◽

pp. 460-472

Author(s):

Kaspar Riesen ◽

Thomas Hanne ◽

Roman Schmidt

Keyword(s):

Edit Distance ◽

User Authentication ◽

String Edit Distance ◽

Distance Model

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String Edit Distance, Random Walks and Graph Matching

Lecture Notes in Computer Science - Structural, Syntactic, and Statistical Pattern Recognition ◽

10.1007/3-540-70659-3_10 ◽

2002 ◽

pp. 104-112 ◽

Cited By ~ 6

Author(s):

Antonio Robles-Kelly ◽

Edwin R. Hancock

Keyword(s):

Random Walks ◽

Edit Distance ◽

Graph Matching ◽

String Edit Distance

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GEOMETRIC APPROACH TO DATA MINING

International Journal of Image and Graphics ◽

10.1142/s0219467801000220 ◽

2001 ◽

Vol 01 (02) ◽

pp. 363-386

Author(s):

WLADIMIR RODRIGUEZ ◽

MARK LAST ◽

ABRAHAM KANDEL ◽

HORST BUNKE

Keyword(s):

Data Mining ◽

Edit Distance ◽

Geometric Approach ◽

Symbolic Representation ◽

Pattern Identification ◽

Curve Matching ◽

Distance Computation ◽

String Edit Distance

In this paper, a new, geometric approach to pattern identification in data mining is presented. It is based on applying string edit distance computation to measuring the similarity between multi-dimensional curves. The string edit distance computation is extended to allow the possibility of using strings, where each element is a vector rather than just a symbol. We discuss an approach for representing 3D-curves using the curvature and the tension as their symbolic representation. This transformation preserves all the information contained in the original 3D-curve. We validate this approach through experiments using synthetic and digitalized data. In particular, the proposed approach is suitable to measure the similarity of 3D-curves invariant under translation, rotation, and scaling. It also can be applied for partial curve matching.

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String Edit Distance

Encyclopedia of Genetics, Genomics, Proteomics and Informatics ◽

10.1007/978-1-4020-6754-9_16249 ◽

2008 ◽

pp. 1890-1890

Keyword(s):

Edit Distance ◽

String Edit Distance

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Phonetic distance and dialect clustering on the Qinghai-Tibet plateau

Linguistics of the Tibeto-Burman Area ◽

10.1075/ltba.17004.pow ◽

2017 ◽

Vol 40 (2) ◽

pp. 161-178

Author(s):

Abe Powell ◽

Hiroyuki Suzuki

Keyword(s):

Edit Distance ◽

Distance Matrix ◽

Tibet Plateau ◽

The Tibetan Plateau ◽

Linguistic Features ◽

Equal Degree ◽

String Edit Distance ◽

Eastern Border ◽

Phonetic Distance ◽

Qinghai Tibet Plateau

Abstract The goal of this paper is to use string edit distance to describe the synchronic relationship between the Tibetan speech varieties located on the Northeastern edge of the Tibetan Plateau. String edit distance provides a statistical way to compare a large number of linguistic features, in essence producing a statistical bundle of isoglosses. In this way, it can be used as a tool in dialect mapping and synchronic clustering. In this paper, the aggregate distance matrix produced by string edit distance reveals that the great degree of phonetic continuity on the grasslands of the northeastern edge of the plateau is matched by an equal degree of phonetic discontinuity in the mountains forming the eastern border of the plateau. While the dialects located on the grasslands can be grouped together into one cluster, the dialects in the mountains can be grouped together into six clusters.

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