Abstract
Wikipedia-centric Knowledge Bases (KBs) such as YAGO and DBpedia store the hyperlinks between articles in Wikipedia using wikilink relations. While wikilinks are signals of semantic connection between entities, the meaning of such connection is most of the times unknown to KBs, e.g., for 89% of wikilinks in DBpedia no other relation between the entities is known. The task of discovering the exact relations that hold between the endpoints of a wikilink is called wik- ilink semantification. In this paper, we apply rule mining techniques on the already semantified wikilinks to propose relations for the unsemantified wikilinks in a subset of DBpedia. By mining highly supported and confident logical rules from KBs, we can semantify wikilinks with very high precision.
| Original language | English |
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| Journal | CEUR Workshop Proceedings |
| Volume | 1409 |
| Publication status | Published - 1 Jan 2015 |
| Event | Workshop on Linked Data on the Web, LDOW 2015 - co-located with the 24th International World Wide Web Conference, WWW 2015 - Florence, Italy Duration: 19 May 2015 → … |