Learning Information Extraction Rules for Semi-Structured and Free Text

被引：84

作者：

Stephen Soderland

机构：

[1] University of Washington,Department Computer Science and Engineering

来源：

Machine Learning | 1999年 / 34卷

关键词：

natural language processing; information extraction; rule learning;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

A wealth of on-line text information can be made available to automatic processing by information extraction (IE) systems. Each IE application needs a separate set of rules tuned to the domain and writing style. WHISK helps to overcome this knowledge-engineering bottleneck by learning text extraction rules automatically.

引用

页码：233 / 272

页数：39

共 7 条

[1] Ashish N.(1997)Wrapper generation for semi-structured Internet sources SIGMOD Record 26 8-15
[2] Knoblock C.(1994)Improving generalization with active learning Machine Learning 15 201-221
[3] Cohn D.(1990)Learning logical definitions from relations Machine Learning 5 239-266
[4] Atlas L.(1984)A theory of the learnable Communications of the ACM 27 1134-1142
[5] Ladner R.(undefined)undefined undefined undefined undefined-undefined
[6] Quinlan J.R.(undefined)undefined undefined undefined undefined-undefined
[7] Valiant L.(undefined)undefined undefined undefined undefined-undefined

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