1999 LearningInfExtrRules

• (Soderland, 1999) ⇒ Stephen Soderland. (1999). “Learning Information Extraction Rules for Semi-Structured and Free Text.” In: Machine Learning, 44(1-3). doi:10.1023/A:1007562322031

Subject Headings: Wrapper Induction Algorithm, Relation Mention Pattern, WHISK System, Learned Information Extraction Pattern.

Cited By

~734 http://scholar.google.com/scholar?cites=4082225710259867250

Quotes

Abtract

• 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.
• WHISK is designed to handle text styles ranging from highly structured to free text, including text that is neither rigidly formatted nor composed of grammatical sentences. Such semi-structured text has largely been beyond the scope of previous systems. When used in conjunction with a syntactic analyzer and semantic tagging, WHISK can also handle extraction from free text such as news stories.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
1999 LearningInfExtrRules	Stephen Soderland			Learning Information Extraction Rules for Semi-Structured and Free Text		Machine Learning (ML) Subject Area	https://eprints.kfupm.edu.sa/48195/1/48195.pdf	10.1023/A:1007562322031		1999