ABSTRACT
Dependency parsing is often used as a component in many text analysis pipelines. However, performance, especially in specialized domains, suffers from the presence of complex terminology. Our hypothesis is that including named entity annotations can improve the speed and quality of dependency parses. As part of BLAH5, we built a web service delivering improved dependency parses by taking into account named entity annotations obtained by third party services. Our evaluation shows improved results and better speed.
Subject(s)
Natural Language ProcessingABSTRACT
DICOM is a standard for data format and transmission of digital medical image. DICOM Data Set is a binary data stream using DICOM encoding rule. DICOM Nesting Data Set is a kind of complex Data Set with a tree structure, and is widely used in DICOM services and encoding of DICOM files for its special structure. In this article, the functions and encoding rule of Data Set and Nesting Data Set in DICOM format are presented, and the way of parsing and organizing of them is put forward. The realization method and practical application are also discussed.