ML Anthology

BoosTexter: A Boosting-Based System for Text Categorization

Robert E. Schapire, Yoram Singer
MLJ 2000 pp. 135-168
doi:10.1023/A:1007649029923 /mlj/2000/schapire2000mlj-boostexter/

Abstract

This work focuses on algorithms which learn from examples to perform multiclass text and speech categorization tasks. Our approach is based on a new and improved family of boosting algorithms. We describe in detail an implementation, called BoosTexter, of the new boosting algorithms for text categorization tasks. We present results comparing the performance of BoosTexter and a number of other text-categorization algorithms on a variety of tasks. We conclude by describing the application of our system to automatic call-type identification from unconstrained spoken customer responses.

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Cite

Text

Schapire and Singer. "BoosTexter: A Boosting-Based System for Text Categorization." Machine Learning, 2000. doi:10.1023/A:1007649029923

Markdown

[Schapire and Singer. "BoosTexter: A Boosting-Based System for Text Categorization." Machine Learning, 2000.](https://mlanthology.org/mlj/2000/schapire2000mlj-boostexter/) doi:10.1023/A:1007649029923

BibTeX

@article{schapire2000mlj-boostexter,
  title     = {{BoosTexter: A Boosting-Based System for Text Categorization}},
  author    = {Schapire, Robert E. and Singer, Yoram},
  journal   = {Machine Learning},
  year      = {2000},
  pages     = {135-168},
  doi       = {10.1023/A:1007649029923},
  volume    = {39},
  url       = {https://mlanthology.org/mlj/2000/schapire2000mlj-boostexter/}
}