Automatic Extraction Rules Generation Based on XPath Pattern Learning

2011 ◽  
pp. 58-69 ◽  
Author(s):  
Jingwei Zhang ◽  
Can Zhang ◽  
Weining Qian ◽  
Aoying Zhou
Keyword(s):  
Pattern Learning ◽  
Automatic Extraction

scholarly journals Automatic Extraction of Appendix from Ultrasonography with Self-Organizing Map and Shape-Brightness Pattern Learning

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Kwang Baek Kim ◽  
Doo Heon Song ◽  
Hyun Jun Park
Keyword(s):  
Learning Algorithm ◽  
Difficult Problem ◽  
Accurate Diagnosis ◽  
Pattern Learning ◽  
Automatic Extraction ◽  
Self Organizing Map ◽  
Neural Learning ◽  
Shape Pattern ◽  
Fully Automatic ◽  
Self Organizing

Accurate diagnosis of acute appendicitis is a difficult problem in practice especially when the patient is too young or women in pregnancy. In this paper, we propose a fully automatic appendix extractor from ultrasonography by applying a series of image processing algorithms and an unsupervised neural learning algorithm, self-organizing map. From the suggestions of clinical practitioners, we define four shape patterns of appendix and self-organizing map learns those patterns in pixel clustering phase. In the experiment designed to test the performance for those four frequently found shape patterns, our method is successful in 3 types (1 failure out of 45 cases) but leaves a question for one shape pattern (80% correct).

Visual cues and spatial pattern learning

2001 ◽  
Author(s):  
Michael F. Brown ◽  
Sue Yang ◽  
Kelly Digian
Keyword(s):  
Spatial Pattern ◽  
Visual Cues ◽  
Pattern Learning

Automatic Extraction of Acronyms from Text

2020 ◽  
Author(s):  
Stuart Yeates
Keyword(s):  
Digital Library ◽  
False Positives ◽  
Automatic Extraction ◽  
False Negatives ◽  
Library Research ◽  
Communications Theory ◽  
Textual Content

A brief introduction to acronyms is given and motivation for extracting them in a digital library environment is discussed. A technique for extracting acronyms is given with an analysis of the results. The technique is found to have a low number of false negatives and a high number of false positives. Introduction Digital library research seeks to build tools to enable access of content, while making as few as possible assumptions about the content, since assumptions limit the range of applicability of the tools. Generally, the broader the assumptions the more widely applicable the tools. For example, keyword based indexing [5] is based on communications theory and applies to all natural human textual languages (allowances for differences in character sets and similar localisation issues not withstanding) . The algorithm described in this paper makes much stronger assumptions about the content. It assumes textual content that contains acronyms, an assumption which is known to hold for...

Sign in / Sign up

Export Citation Format

Share Document