### Abstract

We herein investigate finding unusual patterns from a given string as a text. In the present paper, the pattern is expressed as a substring of the string. The natural assumption with respect to the frequency of a pattern is that the shorter the length of the pattern, the larger the frequency of the pattern. We define a pattern to be pure if the frequencies of all of the substrings of the pattern are the same as the frequency of the pattern. This means that the substrings appear only within the pattern in the string. This condition is in contrast to the natural assumption. The present paper proposes three statistics for quantifying the purity of a pattern, i.e., probability, entropy, and difference, which are calculated based on the frequency of the pattern and its substrings. Experiments using DNA sequences reveal that patterns with large probability correspond to the features of the sequences.

Original language | English |
---|---|

Title of host publication | Proceedings of the 2012 IIAI International Conference on Advanced Applied Informatics, IIAIAAI 2012 |

Pages | 285-290 |

Number of pages | 6 |

DOIs | |

Publication status | Published - Dec 14 2012 |

Event | 1st IIAI International Conference on Advanced Applied Informatics, IIAIAAI 2012 - Fukuoka, Japan Duration: Sep 20 2012 → Sep 22 2012 |

### Publication series

Name | Proceedings of the 2012 IIAI International Conference on Advanced Applied Informatics, IIAIAAI 2012 |
---|

### Other

Other | 1st IIAI International Conference on Advanced Applied Informatics, IIAIAAI 2012 |
---|---|

Country | Japan |

City | Fukuoka |

Period | 9/20/12 → 9/22/12 |

### Fingerprint

### All Science Journal Classification (ASJC) codes

- Information Systems

### Cite this

*Proceedings of the 2012 IIAI International Conference on Advanced Applied Informatics, IIAIAAI 2012*(pp. 285-290). [6337205] (Proceedings of the 2012 IIAI International Conference on Advanced Applied Informatics, IIAIAAI 2012). https://doi.org/10.1109/IIAI-AAI.2012.75

**Mining pure patterns in texts.** / Yamada, Yasuhiro; Nakatoh, Tetsuya; Baba, Kensuke; Ikeda, Daisuke.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*Proceedings of the 2012 IIAI International Conference on Advanced Applied Informatics, IIAIAAI 2012.*, 6337205, Proceedings of the 2012 IIAI International Conference on Advanced Applied Informatics, IIAIAAI 2012, pp. 285-290, 1st IIAI International Conference on Advanced Applied Informatics, IIAIAAI 2012, Fukuoka, Japan, 9/20/12. https://doi.org/10.1109/IIAI-AAI.2012.75

}

TY - GEN

T1 - Mining pure patterns in texts

AU - Yamada, Yasuhiro

AU - Nakatoh, Tetsuya

AU - Baba, Kensuke

AU - Ikeda, Daisuke

PY - 2012/12/14

Y1 - 2012/12/14

N2 - We herein investigate finding unusual patterns from a given string as a text. In the present paper, the pattern is expressed as a substring of the string. The natural assumption with respect to the frequency of a pattern is that the shorter the length of the pattern, the larger the frequency of the pattern. We define a pattern to be pure if the frequencies of all of the substrings of the pattern are the same as the frequency of the pattern. This means that the substrings appear only within the pattern in the string. This condition is in contrast to the natural assumption. The present paper proposes three statistics for quantifying the purity of a pattern, i.e., probability, entropy, and difference, which are calculated based on the frequency of the pattern and its substrings. Experiments using DNA sequences reveal that patterns with large probability correspond to the features of the sequences.

AB - We herein investigate finding unusual patterns from a given string as a text. In the present paper, the pattern is expressed as a substring of the string. The natural assumption with respect to the frequency of a pattern is that the shorter the length of the pattern, the larger the frequency of the pattern. We define a pattern to be pure if the frequencies of all of the substrings of the pattern are the same as the frequency of the pattern. This means that the substrings appear only within the pattern in the string. This condition is in contrast to the natural assumption. The present paper proposes three statistics for quantifying the purity of a pattern, i.e., probability, entropy, and difference, which are calculated based on the frequency of the pattern and its substrings. Experiments using DNA sequences reveal that patterns with large probability correspond to the features of the sequences.

UR - http://www.scopus.com/inward/record.url?scp=84870847112&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84870847112&partnerID=8YFLogxK

U2 - 10.1109/IIAI-AAI.2012.75

DO - 10.1109/IIAI-AAI.2012.75

M3 - Conference contribution

AN - SCOPUS:84870847112

SN - 9780769548265

T3 - Proceedings of the 2012 IIAI International Conference on Advanced Applied Informatics, IIAIAAI 2012

SP - 285

EP - 290

BT - Proceedings of the 2012 IIAI International Conference on Advanced Applied Informatics, IIAIAAI 2012

ER -