Some document genres contain a large num-ber of figures. This position paper outlines approaches to diagram summarization that can augment the many well-developed tech-niques of text summarization. We discuss figures as surrogates for entire documents, thumbnails, extraction, the relations between text and figures as well as how automation might be achieved. The focus is on diagrams (line drawings) because they allow parsing techniques to be used, in contrast to the diffi-culties of general image understanding. We describe the advances in raster image vectori-zation and parsing needed to produce corpora for diagram summarization.
This demo presents a Natural Language Gener-ation (NLG) system that generates summaries of informati...
The task of automatic document summarization aims at generating short summaries for originally long ...
Because of its ability to help users analyze and explore data from a diverse set of domains, visuali...
When documents include graphics such as diagrams, photos, and data plots, the graphics may also requ...
As the information on the internet continues to expand exponentially, machine learning, is becoming ...
Document image analysis is the study of converting documents from paper form to an electronic form t...
Biomedical literature incorporates millions of figures, which are a rich and important knowledge res...
We present a new system for custom summarizations of large text corpora at interactive speed. The ta...
with the huge amount of increase in data thesedays data processing has become very important. It fil...
Identifying and extracting figures and tables along with their captions from scholarly articles is i...
: Medical information is available from a variety of new online resources. Given the number and dive...
The existence of the World Wide Web has caused an information explosion. Readers are overloaded with...
Efficiently exploring a collection of text documents in order to answer a complex question is a chal...
Automatic documet summarization refers to the task of creating document surrogates that are smaller ...
We propose an algorithm to generate graphical summarising of longer text passages using a set of ill...
This demo presents a Natural Language Gener-ation (NLG) system that generates summaries of informati...
The task of automatic document summarization aims at generating short summaries for originally long ...
Because of its ability to help users analyze and explore data from a diverse set of domains, visuali...
When documents include graphics such as diagrams, photos, and data plots, the graphics may also requ...
As the information on the internet continues to expand exponentially, machine learning, is becoming ...
Document image analysis is the study of converting documents from paper form to an electronic form t...
Biomedical literature incorporates millions of figures, which are a rich and important knowledge res...
We present a new system for custom summarizations of large text corpora at interactive speed. The ta...
with the huge amount of increase in data thesedays data processing has become very important. It fil...
Identifying and extracting figures and tables along with their captions from scholarly articles is i...
: Medical information is available from a variety of new online resources. Given the number and dive...
The existence of the World Wide Web has caused an information explosion. Readers are overloaded with...
Efficiently exploring a collection of text documents in order to answer a complex question is a chal...
Automatic documet summarization refers to the task of creating document surrogates that are smaller ...
We propose an algorithm to generate graphical summarising of longer text passages using a set of ill...
This demo presents a Natural Language Gener-ation (NLG) system that generates summaries of informati...
The task of automatic document summarization aims at generating short summaries for originally long ...
Because of its ability to help users analyze and explore data from a diverse set of domains, visuali...