2017
EMNLP
EMNLP 2017
A Short Survey on Taxonomy Learning from Text Corpora: Issues, Resources and Recent Advances
Abstract
AbstractA taxonomy is a semantic hierarchy, consisting of concepts linked by is-a relations. While a large number of taxonomies have been constructed from human-compiled resources (e.g., Wikipedia), learning taxonomies from text corpora has received a growing interest and is essential for long-tailed and domain-specific knowledge acquisition. In this paper, we overview recent advances on taxonomy construction from free texts, reorganizing relevant subtasks into a complete framework. We also overview resources for evaluation and discuss challenges for future research.
🌱
Topic Pioneer
— Ontology Learning
🌉
Interdisciplinary Bridge
— Knowledge & Reasoning and Natural Language Processing
📈
Trend Setter
— Ontology Learning
🧭
Keyword Pioneer
— is-a relation
🐝
Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning