Provision and usage of provenance data in the WebIsALOD Knowledge Graph

URL:	http://ceur-ws.org/Vol-2317/article-06.pdf
Additional URL:	http://ceur-ws.org/Vol-2317/
Document Type:	Conference or workshop publication
Year of publication:	2018
Book title:	CKGSemStats 2018 : Joint Proceedings of the International Workshops on Contextualized Knowledge Graphs, and Semantic Statistics co-located with 17th International Semantic Web Conference (ISWC 2018), Monterey, USA, October 8th, 2018
The title of a journal, publication series:	CEUR Workshop Proceedings
Volume:	2317
Page range:	Article 6
Conference title:	CKGSemStats 2018
Location of the conference venue:	Monterey, CA
Date of the conference:	08.10.2018
Publisher:	Capadisli, Sarven
Place of publication:	Aachen, Germany
Publishing house:	RWTH Aachen
ISSN:	1613-0073
Publication language:	English
Institution:	School of Business Informatics and Mathematics > Web Data Mining (Paulheim 2018-)
Subject:	004 Computer science, internet
Abstract:	The WebIsALOD dataset provides a linked data endpoint to the WebIsA database, which harvests millions of subsumption relations from a large scale Web crawl using text patterns. For each of the relations, the dataset also contains rich provenance data, such as the text pattern used, the original sentence in which the pattern was found, and the source on the Web. In this paper, we describe several alternatives and design decisions for providing statement-level provenance information at large scale for the WebIsALOD dataset. Furthermore, we show the practical impact of that provenance information for computing confidence scores approximating the correctness of each subsumption relation.