Yen et al. proposed automatic personalized knowledge graph (PKG) creation method using Chinese Twitter data,
targeting both explicitly and implicitly mentioned general life events.
Each module was confirmed to work for extracting lifelog events, however, the pipelined system achieved the F1 score of 15.63%, suggesting the difficulty of this task.
Authors
Anzi Yen (National Taiwan University), Hen Hsen Huang, and Hsinhsi Chen (National Chengchi University)
Motivation
Previous work focuses on the detection of major life events such as marriage and graduation.
However, general life events such as dining and visiting a local place remain to be solved.
Proposed method
Proposed system has two stages.
Stage 1: Decide if the tweet contains life events and detect predicates
Stage 2: Extract subject, object, and time.
Results / Insight
Evaluation data: Chinese Twitter data with 18 users (8K tweets).
Personal Knowledge Base Construction from Text-based Lifelogs
Contribution summary
Authors
Motivation
Proposed method
Proposed system has two stages.
Results / Insight