Evolutionary Rule Mining in Time Series Databases

Created by W.Langdon from gp-bibliography.bib Revision:1.4340

  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
  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