Correcting Knowledge Base Assertions
Chen, J., Chen, X., Horrocks, I. , Jimenez-Ruiz, E. 
ORCID: 0000-0002-9083-4599 & Myklebus, E. B. (2020).
Correcting Knowledge Base Assertions.
In:
WWW '20: Proceedings of The Web Conference 2020.
doi: 10.1145/3366423.3380226
Abstract
The usefulness and usability of knowledge bases (KBs) is often limited by quality issues. One common issue is the presence of erroneous assertions, often caused by lexical or semantic confusion. We study the problem of correcting such assertions, and present a general correction framework which combines lexical matching, semantic embedding, soft constraint mining and semantic consistency checking. The framework is evaluated using DBpedia and an enterprise medical KB.
| Publication Type: | Conference or Workshop Item (Paper) |
|---|---|
| Additional Information: | © 2020 IW3C2 (International World Wide Web Conference Committee), published under Creative Commons CC-BY 4.0 License. |
| Publisher Keywords: | Knowledge Base Quality, Assertion Correction, Semantic Embed- ding, Constraint Mining, Consistency Checking |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Departments: | School of Science & Technology > Computer Science |
Available under License Creative Commons Attribution.
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