Evolving Text Classification Rules with Genetic Programming

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@Article{journals/aai/HirschSH05,

• title = "Evolving Text Classification Rules with Genetic Programming",
• author = "Laurence Hirsch and Masoud Saeedi and Robin Hirsch",
• journal = "Applied Artificial Intelligence",
• year = "2005",
• number = "7",
• volume = "19",
• pages = "659--676",
• month = aug,
• bibdate = "2005-12-01",
• bibsource = "DBLP, http://dblp.uni-trier.de/db/journals/aai/aai19.html#HirschSH05",
• keywords = "genetic algorithms, genetic programming",
• URL = "http://www.journalsonline.tandf.co.uk/openurl.asp?genre=article&issn=0883-9514&volume=19&issue=7&spage=659",
• DOI = "doi:10.1080/08839510590967307",
• abstract = "We describe a novel method for using genetic programming to create compact classification rules using combinations of N-grams (character strings). Genetic programs acquire fitness by producing rules that are effective classifiers in terms of precision and recall when evaluated against a set of training documents. We describe a set of functions and terminals and provide results from a classification task using the Reuters 21578 dataset. We also suggest that the rules may have a number of other uses beyond classification and provide a basis for text mining applications.",

}

Genetic Programming entries for Laurence Hirsch Masoud Saeedi Robin Hirsch

Citations