Learning methods for combining linguistic indicators to classify verbs

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{siegel:1997:lmclicv,

• author = "Eric V. Siegel",
• title = "Learning methods for combining linguistic indicators to classify verbs",
• booktitle = "Proceedings of the Second Conference on Empirical Methods in Natural Language Processing",
• year = "1997",
• address = "Providence, RI, USA",
• month = aug,
• keywords = "genetic algorithms, genetic programming",
• URL = "http://www.cs.columbia.edu/~evs/papers/stativity.ps",
• abstract = "Fourteen linguistically-motivated numerical indicators are evaluated for their ability to categorize verbs as either states or events. The values for each indicator are computed automatically across a corpus of text. To improve classification performance, machine learning techniques are employed to combine multiple indicators. Three machine learning methods are compared for this task: decision tree induction, a genetic algorithm, and log-linear regression.",

}

Genetic Programming entries for Eric Siegel

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