Introduction to special issue on machine learning approaches to shallow parsing

被引:21
|
作者
Hammerton, J [1 ]
Osborne, M
Armstrong, S
Daelemans, W
机构
[1] Univ Groningen, Alfa Informat, NL-9700 AB Groningen, Netherlands
[2] Univ Edinburgh, Div Informat, Edinburgh EH8 9YL, Midlothian, Scotland
[3] Univ Geneva, ISSCO, ETI, CH-1211 Geneva, Switzerland
[4] Univ Antwerp, B-2020 Antwerp, Belgium
关键词
All Open Access; Green;
D O I
10.1162/153244302320884533
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This article introduces the problem of partial or shallow parsing (assigning partial syntactic structure to sentences) and explains why it is an important natural language processing (NLP) task. The complexity of the task makes Machine Learning an attractive option in comparison to the handcrafting of rules. On the other hand, because of the same task complexity, shallow parsing makes an excellent benchmark problem for evaluating machine learning algorithms. We sketch the origins of shallow parsing as a specific task for machine learning of language, and introduce the articles accepted for this special issue, a representative sample of current research in this area. Finally, future directions for machine learning of shallow parsing are suggested.
引用
收藏
页码:551 / 558
页数:8
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