Evolutionary Rule Mining in Time Series Databases

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@Article{hetland:2005:ML,

• author = "Magnus Lie Hetland and Pal Saetrom",
• title = "Evolutionary Rule Mining in Time Series Databases",
• journal = "Machine Learning",
• year = "2005",
• volume = "58",
• number = "2-3",
• pages = "107--125",
• month = feb,
• keywords = "genetic algorithms, genetic programming, sequence mining, knowledge discovery, time series, specialised hardware",
• ISSN = "0885-6125",
• DOI = "doi:10.1007/s10994-005-5823-8",
• abstract = "Data mining in the form of rule discovery is a growing field of investigation. A recent addition to this field is the use of evolutionary algorithms in the mining process. While this has been used extensively in the traditional mining of relational databases, it has hardly, if at all, been used in mining sequences and time series. In this paper we describe our method for evolutionary sequence mining, using a specialized piece of hardware for rule evaluation, and show how the method can be applied to several different mining tasks, such as supervised sequence prediction, unsupervised mining of interesting rules, discovering connections between separate time series, and investigating tradeoffs between contradictory objectives by using multiobjective evolution.",

}

Genetic Programming entries for Magnus Lie Hetland Pal Saetrom

Citations