The method of N-grams in large-scale clustering of DNA texts

Z. Volkovich; V. Kirzhner; A. Bolshoy; E. Nevo; A. Korol

doi:10.1016/j.patcog.2005.05.002

The method of N-grams in large-scale clustering of DNA texts

Z. Volkovich, V. Kirzhner, A. Bolshoy, E. Nevo, A. Korol

Department of Evolutionary and Environmental Biology

Research output: Contribution to journal › Article › peer-review

Abstract

This paper is devoted to the techniques of clustering of texts based on the comparison of vocabularies of N-grams. In contrast to the regular N-grams approach, the proposed N-grams method is based on calculation of imperfect occurrences of N-grams in a text up to a number of mismatched strings. We demonstrated that such an approach essentially improves the resolving capacity of the N-grams method for DNA texts. Additionally, we discuss a mutual usage scheme of different clustering technique types to verify the partition quality.

Original language	English
Pages (from-to)	1902-1912
Number of pages	11
Journal	Pattern Recognition
Volume	38
Issue number	11
DOIs	https://doi.org/10.1016/j.patcog.2005.05.002
State	Published - Nov 2005

Keywords

Clustering
Compositional spectra
Genome comparisons
N-grams
Strings mismatching

ASJC Scopus subject areas

Software
Signal Processing
Computer Vision and Pattern Recognition
Artificial Intelligence

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10.1016/j.patcog.2005.05.002

Cite this

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abstract = "This paper is devoted to the techniques of clustering of texts based on the comparison of vocabularies of N-grams. In contrast to the regular N-grams approach, the proposed N-grams method is based on calculation of imperfect occurrences of N-grams in a text up to a number of mismatched strings. We demonstrated that such an approach essentially improves the resolving capacity of the N-grams method for DNA texts. Additionally, we discuss a mutual usage scheme of different clustering technique types to verify the partition quality.",

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AU - Kirzhner, V.

AU - Bolshoy, A.

AU - Nevo, E.

AU - Korol, A.

PY - 2005/11

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AB - This paper is devoted to the techniques of clustering of texts based on the comparison of vocabularies of N-grams. In contrast to the regular N-grams approach, the proposed N-grams method is based on calculation of imperfect occurrences of N-grams in a text up to a number of mismatched strings. We demonstrated that such an approach essentially improves the resolving capacity of the N-grams method for DNA texts. Additionally, we discuss a mutual usage scheme of different clustering technique types to verify the partition quality.

KW - Clustering

KW - Compositional spectra

KW - Genome comparisons

KW - N-grams

KW - Strings mismatching

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JO - Pattern Recognition

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ER -

The method of N-grams in large-scale clustering of DNA texts

Abstract

Keywords

ASJC Scopus subject areas

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