Papers with real DBpedia datasets

1 papers
Attributed and Predictive Entity Embedding for Fine-Grained Entity Typing in Knowledge Bases (C18-1)

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Challenge: Existing methods for identifying semantic type of entities are incomplete even in large knowledge bases.
Approach: They propose an attributed and predictive entity embedding method which can fully utilize various kinds of information comprehensively.
Outcome: Experiments on two real DBpedia datasets show that the proposed method outperforms 8 state-of-the-art methods with 4.0% improvement in Mi-F1 and 5.2% improvement in Ma-F1.

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