The Management of Context-Sensitive Features: A Review of Strategies
<|reference_start|>The Management of Context-Sensitive Features: A Review of Strategies: In this paper, we review five heuristic strategies for handling context-sensitive features in supervised machine learning from examples. We discuss two methods for recovering lost (implicit) contextual information. We mention some evidence that hybrid strategies can have a synergetic effect. We then show how the work of several machine learning researchers fits into this framework. While we do not claim that these strategies exhaust the possibilities, it appears that the framework includes all of the techniques that can be found in the published literature on contextsensitive learning.<|reference_end|>
@article{turney2002the,
    title={The Management of Context-Sensitive Features: A Review of Strategies},
    author={Peter D. Turney (National Research Council of Canada)},
    journal={13th International Conference on Machine Learning, Workshop on
  Learning in Context-Sensitive Domains, Bari, Italy, (1996), 60-66},
    year={2002},
    number={NRC-39221},
    archivePrefix={arXiv},
    eprint={cs/0212037},
    primaryClass={cs.LG cs.CV}
}