Publication:
Structure-based rule selection framework for association rule mining of traffic accident data

Issued Date

2007-12-01

Resource Type

Conference Paper

DOI

10.1109/ICCIAS.2006.294241

Other identifier(s)

2-s2.0-38549181507

Rights

Mahidol University

Rights Holder(s)

SCOPUS

Bibliographic Citation

2006 International Conference on Computational Intelligence and Security, ICCIAS 2006. Vol.1, (2007), 781-784

Suggested Citation

Rangsipan Marukatat Structure-based rule selection framework for association rule mining of traffic accident data. 2006 International Conference on Computational Intelligence and Security, ICCIAS 2006. Vol.1, (2007), 781-784. doi:10.1109/ICCIAS.2006.294241 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/24379

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Title

Structure-based rule selection framework for association rule mining of traffic accident data

Author(s)

Rangsipan Marukatat

Other Contributor(s)

Mahidol University

Abstract

A rule selection framework is proposed which classifies, selects, and filters out association rules based on the analysis of the rule structures. It was applied to real traffic accident data collected from local police stations. The rudimentary nature of the data required several passes of association rule mining to be performed, each with different sets of parameters, so that semantically interesting rules can be spotted from the pool of results. It was shown that the proposed framework could find candidate rules that offer some insight into the phenomena being studied. © 2006 IEEE.

Keyword(s)

Computer Science
 Engineering

Availability

URI

https://repository.li.mahidol.ac.th/handle/20.500.14594/24379

Collections

Scopus 2006-2010