Handling Sparse Data by Successive Abstraction
<|reference_start|>Handling Sparse Data by Successive Abstraction: A general, practical method for handling sparse data that avoids held-out data and iterative reestimation is derived from first principles. It has been tested on a part-of-speech tagging task and outperformed (deleted) interpolation with context-independent weights, even when the latter used a globally optimal parameter setting determined a posteriori.<|reference_end|>
@article{samuelsson1996handling,
    title={Handling Sparse Data by Successive Abstraction},
    author={Christer Samuelsson (University of the Saarland)},
    journal={Coling 96},
    year={1996},
    number={CLAUS 69},
    archivePrefix={arXiv},
    eprint={cmp-lg/9605034},
    primaryClass={cmp-lg cs.CL}
}