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| Wenmai—A Probablistic-Like Association Reliable Chinese Knowledge Graph |
| LI Wenhao1,2,3, LIU Wenchang2,3,4, SUN Maosong1,2,3,5, YI Xiaoyuan6 |
1.The Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China;
2.Institute for Artificial Intelligence, Tsinghua University, Beijing 100084, China;
3.Beijing National Center for Information Science and Technology, Beijing 100084, China;
4.The Department of Computer Science, University of California, Davis, Davis, CA 95616, USA;
5.Jiangsu Collaborative Innovation Center for Language Ability, Jiangsu Normal University, Xuzhou, Jiangsu 221009, China;
6.Microsoft Research Asia, Beijing 100080, China |
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Abstract The existing Chinese knowledge graphs are derived from Wikipedia and Baidu Baike by leveraging the information of the entity infobox and categorical system. Differently,This article proposes a Chinese knowledge graph with probabilistic links by treat the hyperlinks in these resources as entity relations, weighted by the TF-IDF value of the mention frequency of the target entity in the entry article of the source entity. A reliable link screening algorithm is further desgned to remove the occasional links to make the knowledge graph more reliable. Based on the above methods, this article has constructed a probabilistically probabilistic-like association reliable Chinese knowledge graph named "Wenmai", which is public available in GitHub as a support for knowledge-guided natural language processing.
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Received: 19 October 2021
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2022, Vol. 36 
