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- W202389787 abstract "Type information is very valuable in knowledge bases. However, most large open knowledge bases are incomplete with respect to type information, and, at the same time, contain noisy and incorrect data. That makes classic type inference by reasoning difficult. In this paper, we propose the heuristic link-based type inference mechanism SDType, which can handle noisy and incorrect data. Instead of leveraging T-box information from the schema, SDType takes the actual use of a schema into account and thus is also robust to misused schema elements." @default.
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- W202389787 date "2013-01-01" @default.
- W202389787 modified "2023-09-24" @default.
- W202389787 title "Type Inference on Noisy RDF Data" @default.
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- W202389787 doi "https://doi.org/10.1007/978-3-642-41335-3_32" @default.
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