A Corrective Training Algorithm for Adaptive Learning in Bag Generation

Details A Corrective Training Algorithm for Adaptive Learning in Bag Generation A Corrective Training Algorithm for Adaptive Learning in Bag Generation

1994-07-06

arxiv.org/abs/cmp-lg/9407005v1

proceedings of NeMLaP-94

Computer Science

Computation and Language

7 pages, uuencoded compressed PostScript file; extract with Unix uudecode and uncompress

Scientific paper

The sampling problem in training corpus is one of the major sources of errors in corpus-based applications. This paper proposes a corrective training algorithm to best-fit the run-time context domain in the application of bag generation. It shows which objects to be adjusted and how to adjust their probabilities. The resulting techniques are greatly simplified and the experimental results demonstrate the promising effects of the training algorithm from generic domain to specific domain. In general, these techniques can be easily extended to various language models and corpus-based applications.

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