Unsupervised Information Extraction by Text Segmentation

A new unsupervised approach to the problem of Information Extraction by Text Segmentation (IETS) is proposed, implemented and evaluated herein. The authors’ approach relies on information available on pre—existing data to learn how to associate segments in the input string with attributes of a given domain relying on a very effective set of content—based features. The effectiveness of the content—based features is also exploited to directly learn from test data structure—based features, wit...