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題名:	Personal Knowledge Base Construction from Text-based Lifelogs
作者:	黃瀚萱 Huang, Hen-Hsen Yen, An-Zi Chen, Hsin-Hsi
貢獻者:	資科系
關鍵詞:	Lifelogging;Life event detection;Personal knowledge base construction;Social media
日期:	2019-07
上傳時間:	2021-06-04 14:44:54 (UTC+8)
摘要:	Previous work on lifelogging focuses on life event extraction from image, audio, and video data via wearable sensors. In contrast to wearing an extra camera to record daily life, people are used to log their life on social media platforms. In this paper, we aim to extract life events from textual data shared on Twitter and construct personal knowledge bases of individuals. The issues to be tackled include (1) not all text descriptions are related to life events, (2) life events in a text description can be expressed explicitly or implicitly, (3) the predicates in the implicit events are often absent, and (4) the mapping from natural language predicates to knowledge base relations may be ambiguous. A joint learning approach is proposed to detect life events in tweets and extract event components including subjects, predicates, objects, and time expressions. Finally, the extracted information is transformed to knowledge base facts. The evaluation is performed on a collection of lifelogs from 18 Twitter users. Experimental results show our proposed system is effective in life event extraction, and the constructed personal knowledge bases are expected to be useful to memory recall applications.
關聯:	Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, Association for Computing Machinery, pp.185-194
資料類型:	conference
DOI 連結:	https://dl.acm.org/doi/10.1145/3331184.3331209
DOI:	10.1145/3331184.3331209
顯示於類別:	[資訊科學系] 會議論文

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