A serious bottleneck in the development of trainable text summarization systems is the shortage of training data. Constructing such data is a very tedious task, especially because...
Most supervised language processing systems show a significant drop-off in performance when they are tested on text that comes from a domain significantly different from the domai...
Researchers have developed many models to predict and understand human performance in text entry. Most of the models are specific to a technology or fail to account for human fact...
Research on linear text segmentation has been an on-going focus in NLP for the last decade, and it has great potential for a wide range of applications such as document summarizati...
Jingbo Zhu, Na Ye, Xinzhi Chang, Wenliang Chen, Be...
Natural scene images brought new challenges for a few years and one of them is text understanding over images or videos. Text extraction which consists to segment textual foregrou...