6533b824fe1ef96bd1281315
RESEARCH PRODUCT
Extracting Semantic Knowledge from Unstructured Text Using Embedded Controlled Language
Normunds GruzitisBrian DavisRamona EnacheHazem Safwatsubject
Information retrievalConcept searchNoisy text analyticsbusiness.industryComputer scienceText simplification010401 analytical chemistryText graph02 engineering and technologycomputer.software_genre01 natural scienceslanguage.human_language0104 chemical sciencesInformation extractionControlled natural languageKnowledge extractionExplicit semantic analysis0202 electrical engineering electronic engineering information engineeringlanguage020201 artificial intelligence & image processingArtificial intelligencebusinesscomputerNatural language processingdescription
Nowadays, most of the data on the Web is still in the form of unstructured text. Knowledge extraction from unstructured text is highly desirable but extremely challenging due to the inherent ambiguity of natural language. In this article, we present an architecture of an information extraction system based on the concept of Embedded Controlled Language that allows for extracting formal semantic knowledge from an unstructured text corpus. Moreover, the presented approach has a potential to support multilingual input and output.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2016-02-01 | 2016 IEEE Tenth International Conference on Semantic Computing (ICSC) |