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HIRSCH, Laurence, SAEEDI, M and HIRSCH, R (2005). Evolving rules for document classification. In: Genetic programming. Lecture Notes in Computer Science (3447). Berlin, Springer, 85-95.
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Abstract
We describe a novel method for using Genetic Programming to create compact classification rules based on 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 because the induced rules are meaningful to a human analyst they may have a number of other uses beyond classification and provide a basis for text mining applications.
| Item Type: | Book Section |
|---|---|
| Additional Information: | 8th European Conference, EuroGP 2005, Lausanne, Switzerland, March 30 - April 1, 2005. Proceedings |
| Research Institute, Centre or Group - Does NOT include content added after October 2018: | Cultural Communication and Computing Research Institute > Communication and Computing Research Centre |
| Departments - Does NOT include content added after October 2018: | Faculty of Science, Technology and Arts > Department of Computing |
| Identification Number: | https://doi.org/10.1007/978-3-540-31989-4_8 |
| Page Range: | 85-95 |
| Depositing User: | Laurence Hirsch |
| Date Deposited: | 25 Feb 2013 16:37 |
| Last Modified: | 18 Mar 2021 14:02 |
| URI: | https://shura.shu.ac.uk/id/eprint/6622 |
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