Narratives are fundamental to our understanding of the world, providing us with a natural
structure for knowledge representation over time. Computational narrative extraction is a …

Improving disaster management and recovery techniques is one of national priorities given
the huge toll caused by man-made and nature calamities. Data-driven disaster management …

We design a class of submodular functions meant for document summarization tasks. These
functions each combine two terms, one which encourages the summary to be representative …

When writing a summary, humans tend to choose content from one or two sentences and
merge them into a single summary sentence. However, the mechanisms behind the …

This paper presents GFlow, a novel system for coherent extractive multi-document
summarization (MDS). 1 Where previous work on MDS considered sentence selection and …

We introduce a method to learn a mixture of submodular" shells" in a large-margin setting. A
submodular shell is an abstract submodular function that can be instantiated with a ground …

We introduce a supervised model for predicting word importance that incorporates a rich set
of features. Our model is superior to prior approaches for identifying words used in human …

The rise in the amount of textual resources available on the Internet has created the need for
tools of automatic document summarization. The main challenges of query-oriented …

Microblogging service has emerged to be a dominant web medium for billions of individuals
sharing and spreading instant news and information, therefore monitoring the event …

The most important obstacles facing multi-document summarization include excessive
redundancy in source descriptions and the looming shortage of training data. These …