Automatic Relation Extraction from Text: A Survey
Kun Li, Junsheng Zhang, Changqing Yao, Chongde Shi · 2016
Relation extraction is an important task for understanding text. In the big data era, automatic relation extraction from unstructured texts is urgently needed for structured information organization and information analysis. In this paper, we survey the automatic relation extraction methods, especially the traditional machine learning on closed data set and open information environment such as Web, including supervised and semi-supervised methods. And then, we discuss the applications based on relation extraction such as event extraction and QA systems.