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Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/145431

Title:	A Multi-grained Dataset for News Event Triggered Knowledge Update
Authors:	鄭宇君 Cheng, Yu chung Lee, Yu Ting;Tang, Ying Jhe;Chen, Pailin;Li, Tsai Yen;Huang, Hen Hsen
Contributors:	傳播學院
Date:	2022-10
Issue Date:	2023-06-16 16:42:08 (UTC+8)
Abstract:	Keeping knowledge facts up-to-date is labored and costly as the world rapidly changes and new information emerges every second. In this work, we introduce a novel task, news event triggered knowledge update. Given an existing article about a topic with a news event about the topic, the aim of our task is to generate an updated article according to the information from the news event. We create a multi-grained dataset for the investigation of our task. The articles from Wikipedia are collected and aligned with news events at multiple language units, including the citation text, the first paragraph, and the full content of the news article. Baseline models are also explored at three levels of knowledge update, including the first paragraph, the summary, and the full content of the knowledge facts.
Relation:	CIKM `22: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, ACM, pp.4158-4162
Data Type:	conference
DOI 連結:	https://doi.org/10.1145/3511808.3557537
DOI:	10.1145/3511808.3557537
Appears in Collections:	[傳播學院] 會議論文

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