Harvesting Organization Linked Data from the Web

Zhongguang Zheng, Yingju Xia, Lu Fang, Yao Meng, Jun Sun

2018

Abstract

In this paper, we describe our approach of automatically extracting property-value pairs from the Web for organizations when only the name and address information are known. In order to explore the enormous knowledge from the Web, we first retrieve the Web pages containing organization properties by search engine, and then automatically extract the property-value pairs regardless of heterogeneous Web page structures. Our method does not require any training data or human-made template. We have constructed an organization knowledge base containing 3 million entities extracted from the Web for 4.2 million organizations which only have name and address information. The experiment shows that our approach makes it possible and effective for people to construct their own knowledge base.

Paper Citation

in Harvard Style

Zheng Z., Xia Y., Fang L., Meng Y. and Sun J. (2018). Harvesting Organization Linked Data from the Web. In Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2018) - Volume 2: KEOD; ISBN 978-989-758-330-8, SciTePress, pages 159-166. DOI: 10.5220/0006888101590166

in Bibtex Style

@conference{keod18,
author={Zhongguang Zheng and Yingju Xia and Lu Fang and Yao Meng and Jun Sun},
title={Harvesting Organization Linked Data from the Web},
booktitle={Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2018) - Volume 2: KEOD},
year={2018},
pages={159-166},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006888101590166},
isbn={978-989-758-330-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2018) - Volume 2: KEOD
TI - Harvesting Organization Linked Data from the Web
SN - 978-989-758-330-8
AU - Zheng Z.
AU - Xia Y.
AU - Fang L.
AU - Meng Y.
AU - Sun J.
PY - 2018
SP - 159
EP - 166
DO - 10.5220/0006888101590166
PB - SciTePress