Handling Sparse Data by Successive Abstraction

Details Handling Sparse Data by Successive Abstraction Handling Sparse Data by Successive Abstraction

1996-05-29

arxiv.org/abs/cmp-lg/9605034v1

Coling 96

Computer Science

Computation and Language

6 pages, uuencoded, gzipped PostScript

Scientific paper

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.

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