Correcting Knowledge Base Assertions
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| Authors | Ernesto Jimenez-Ruiz, Erik B. Myklebus, Xi Chen, Ian Horrocks, Jiaoyan Chen |
| Journal/Conference Name | The Web Conference 2020 - Proceedings of the World Wide Web Conference, WWW 2020 |
| Paper Category | Artificial Intelligence |
| Paper 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. |
| Date of publication | 2020 |
| Code Programming Language | Python |
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