Popular knowledge graphs such as DBpedia and YAGO are built from Wikipedia, and therefore similar in coverage. In contrast, Wikifarms like Fandom contain Wikis for specific topics, which are often complementary to the information contained in Wikipedia, and thus DBpedia and YAGO. Extracting these Wikis with the DBpedia extraction framework is possible, but results in many isolated knowledge graphs. In this paper, we show how to create one consolidated knowledge graph, called DBkWik, from thousands of Wikis. We perform entity resolution and schema matching, and show that the resulting large-scale knowledge graph is complementary to DBpedia.
Description
DBkWik: A Consolidated Knowledge Graph from Thousands of Wikis | IEEE Conference Publication | IEEE Xplore
%0 Conference Paper
%1 8588770
%A Hertling, Sven
%A Paulheim, Heiko
%B 2018 IEEE International Conference on Big Knowledge (ICBK)
%D 2018
%K knowledgegraph metadata ontologie
%P 17-24
%R 10.1109/ICBK.2018.00011
%T DBkWik: A Consolidated Knowledge Graph from Thousands of Wikis
%X Popular knowledge graphs such as DBpedia and YAGO are built from Wikipedia, and therefore similar in coverage. In contrast, Wikifarms like Fandom contain Wikis for specific topics, which are often complementary to the information contained in Wikipedia, and thus DBpedia and YAGO. Extracting these Wikis with the DBpedia extraction framework is possible, but results in many isolated knowledge graphs. In this paper, we show how to create one consolidated knowledge graph, called DBkWik, from thousands of Wikis. We perform entity resolution and schema matching, and show that the resulting large-scale knowledge graph is complementary to DBpedia.
@inproceedings{8588770,
abstract = {Popular knowledge graphs such as DBpedia and YAGO are built from Wikipedia, and therefore similar in coverage. In contrast, Wikifarms like Fandom contain Wikis for specific topics, which are often complementary to the information contained in Wikipedia, and thus DBpedia and YAGO. Extracting these Wikis with the DBpedia extraction framework is possible, but results in many isolated knowledge graphs. In this paper, we show how to create one consolidated knowledge graph, called DBkWik, from thousands of Wikis. We perform entity resolution and schema matching, and show that the resulting large-scale knowledge graph is complementary to DBpedia.},
added-at = {2024-11-18T15:41:13.000+0100},
author = {Hertling, Sven and Paulheim, Heiko},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/25dcdffeb37c3d8d21c77fcdf2106c11d/diglezakis},
booktitle = {2018 IEEE International Conference on Big Knowledge (ICBK)},
description = {DBkWik: A Consolidated Knowledge Graph from Thousands of Wikis | IEEE Conference Publication | IEEE Xplore},
doi = {10.1109/ICBK.2018.00011},
interhash = {e8d238a941800c37e7c4af58c3efa322},
intrahash = {5dcdffeb37c3d8d21c77fcdf2106c11d},
keywords = {knowledgegraph metadata ontologie},
month = nov,
pages = {17-24},
timestamp = {2024-11-18T15:41:13.000+0100},
title = {DBkWik: A Consolidated Knowledge Graph from Thousands of Wikis},
year = 2018
}
