- Abstract:
-
The Open Information Extraction Project is one of the most ambitious attempts in the area of automated constructed ontologies by harvesting information from the web. What we will call their KnowItAll Ontology contains about 6 billion items, consisting of triples and rules. The downside of such automatically constructed ontologies is that they contain a vast number of errors: some arising from errors in the original web data and some from errors in extracting the data. In this project we explore whether techniques we have developed in the domain of ontology repair can be used to detect and correct some of these errors. In particular, we explore whether (i) the errors in the KnowItAll Ontology can be automatically detected by using a theorem prover to nd inconsistencies; (ii) the errors can be classi ed; and (iii) ontology repair techniques may be used to automatically correct the errors, based on their classi cation.
- Links To Paper
- No links available
- Bibtex format
- @Misc{EDI-INF-RR-1411,
- author = {
Andriana Gkaniatsou
and Alan Bundy
and Fiona McNeill
},
- title = {Towards the automatic detection and correction of errors in automatically constructed ontologies},
- year = 2012,
- }
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