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VICKEY: Mining Conditional Keys on Knowledge Bases

Danai Symeonidou; Luis Galárraga; Nathalie Pernelle; Fatiha Saïs; Fabian Suchanek

A conditional key is a key constraint that is valid in only a part of the data. In this paper, we show how such keys can be mined automatically on large knowledge bases (KBs). For this, we combine techniques from key mining with techniques from rule mining. We show that our method can scale to KBs of millions of facts. We also show that the conditional keys we mine can improve the quality of entity linking by up to 47 percentage points.

This research was supported by the grants ANR-11-LABEX-0045-DIGICOSM, ANR-16-CE23-0007-01 (DICOS'), the "Machine Learning for Big Data'' of Télécom ParisTech, and by the AGINFRA+ project (Grant Agreement no. 731001).
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