Entity Classification for Military Knowledge Graph based on Baidu Encyclopedia Distance Learning

Huiran Jia, Yuan Li, Dandan Song, Qinglin Wang

科研成果: 书/报告/会议事项章节会议稿件同行评审

1 引用 (Scopus)

摘要

Entity types are a critical enabler for many NLP tasks that use KGs as a reference source. However, Classifying terminological entities without context remains an important outstanding obstacle in the field of KG completion. In this paper, we put forward a method combining distance learning and deep learning to address the classification of entity with no context. We compare the performance of our method with several text classification methods and shows our approach is empirically effective. Furthermore, the experiment result shows our approach can reduce the labeling work cost and expand the entities for further knowledge graph construction.

源语言英语
主期刊名Proceedings of 18th International Bhurban Conference on Applied Sciences and Technologies, IBCAST 2021
编辑Muhammad Zafar-Uz-Zaman, Naveed A. Siddiqui, Mazhar Iqbal, Abdur Rauf, Naeem Zafar, Usman Qayyum, Tahir Jamil, Saifullah Khan, Irfan Ali, Qaisar Ahsan, Sajjad Asghar, Mureed Hussian, Shiraz Ahmad, Muhammad Rafique, Naveed Durrani, Shafiq R. Qureshi, Syed Ali Abbas, Naveed Ahsan, Abdul Mueed
出版商Institute of Electrical and Electronics Engineers Inc.
366-371
页数6
ISBN(电子版)9780738105352
DOI
出版状态已出版 - 12 1月 2021
活动18th International Bhurban Conference on Applied Sciences and Technologies, IBCAST 2021 - Virtual, Islamabad, 巴基斯坦
期限: 12 1月 202116 1月 2021

出版系列

姓名Proceedings of 18th International Bhurban Conference on Applied Sciences and Technologies, IBCAST 2021

会议

会议18th International Bhurban Conference on Applied Sciences and Technologies, IBCAST 2021
国家/地区巴基斯坦
Virtual, Islamabad
时期12/01/2116/01/21

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