In this paper, we present a novel framework for machine learning-based cross-media knowledge extraction. The framework is specifically designed to handle documents composed of th...
A labeled sequence data set related to a certain biological property is often biased and, therefore, does not completely capture its diversity in nature. To reduce this sampling b...
Information extraction is concerned with the location of specific items in (unstructured) textual documents, e.g., being applied for the acquisition of structured data. Then, the ...
Traditional methods for data mining typically make the assumption that data is centralized and static. This assumption is no longer tenable. Such methods waste computational and I/...
Adriano Veloso, Matthew Eric Otey, Srinivasan Part...
Component-based enterprise systems often suffer from performance issues as a result of poor system design. In this paper, we propose a framework to automatically detect, assess an...