Building Structured Databases of Factual Knowledge from Massive Text Corpora
Xiang Ren, Meng Jiang, Jingbo Shang, Jiawei Han · 2017
In today's computerized and information-based society, people are inundated with vast amounts of text data, ranging from news articles, social media post, scientific publications, to a wide range of textual information from various domains (corporate reports, advertisements, legal acts, medical reports). To turn such massive unstructured text data into structured, actionable knowledge, one of the grand challenges is to gain an understanding of the factual information (e.g., entities, attributes, relations) in the text.