Handling Sparse Data by Successive Abstraction
cmp-lg
2008-02-03 v1 计算与语言
摘要
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.
引用
@article{arxiv.cmp-lg/9605034,
title = {Handling Sparse Data by Successive Abstraction},
author = {Christer Samuelsson},
journal= {arXiv preprint arXiv:cmp-lg/9605034},
year = {2008}
}
备注
6 pages, uuencoded, gzipped PostScript