Personal Knowledge Base Construction from Text-based Lifelogs.
Journal
Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2019, Paris, France, July 21-25, 2019.
Pages
185-194
Date Issued
2019
Author(s)
Abstract
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.
Type
conference paper