This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
Jie Cheng, Russell Greiner, Jonathan Kelly, David ...
Clinical medical records contain a wealth of information, largely in free-text form. Means to extract structured information from free-text records is an important research endeav...
Xiaohua Zhou, Hyoil Han, Isaac Chankai, Ann Prestr...
As the Web provides rich data embedded in the immense contents inside pages, we witness many ad-hoc efforts for exploiting fine granularity information across Web text, such as We...
Background: In the analysis of networks we frequently require the statistical significance of some network statistic, such as measures of similarity for the properties of interact...
Automatically segmenting unstructured text strings into structured records is necessary for importing the information contained in legacy sources and text collections into a data ...