Using GUHA Data Mining Method in Analyzing Road Traffic Accidents Occurred in the Years 2004–2008 in Finland

Esko Turunen

doi:10.1007/s41019-017-0044-2

Using GUHA Data Mining Method in Analyzing Road Traffic Accidents Occurred in the Years 2004–2008 in Finland

Esko Turunen

Tutkimustuotos: Artikkeli › Tieteellinen › vertaisarvioitu

13 Sitaatiot (Scopus)

44 Lataukset (Pure)

Abstrakti

The suitability of the GUHA data mining method in analyzing a big data matrix is studied in this report in general, and, in particular, a data matrix containing more than 80,000 road traffic accidents occurred in Finland in 2004–2008 is examined by LISp-Miner, a software implementation of GUHA. The general principles of GUHA are first outlined, and then, the road accident data is analyzed. As a result, more than 10,000 associations and dependencies, called hypothesis in the GUHA language, were found; some easily understandable of them are presented here. Our conclusion is that the GUHA method is useful, in particular when one wants to explore relatively small size, but still significant dependencies in a given large data matrix.

Alkuperäiskieli	Englanti
Sivut	224-231
Sivumäärä	8
Julkaisu	Data Science and Engineering
Vuosikerta	2
Numero	3
DOI - pysyväislinkit	https://doi.org/10.1007/s41019-017-0044-2
Tila	Julkaistu - 27 marrask. 2017
OKM-julkaisutyyppi	A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

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10.1007/s41019-017-0044-2Lisenssi: CC BY

s41019-017-0044-2
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Final published version, 382 KBLisenssi: CC BY

http://urn.fi/URN:NBN:fi:tty-201712142364Lisenssi: CC BY

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author = "Esko Turunen",

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doi = "10.1007/s41019-017-0044-2",

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Using GUHA Data Mining Method in Analyzing Road Traffic Accidents Occurred in the Years 2004–2008 in Finland

Abstrakti

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