The day-to-day growth of online information necessitates intensive research in automatic text summarization (ATS). ATS software produces summary by extracting important from the original text. With help summaries, users can easily read and understand documents interest. Most approaches for used only local properties Moreover, numerous make sentence selection difficult complicated. So this artic...

As the amount of available digital video content is increasing exponentially, novel ways of storing, accessing and retrieving it are being developped, such as indexing, segmentation or abstraction techniques. Video abstraction can be useful in many ways – from automatic home movie editing to easier (and faster) exploration of a video collection. Video summaries can be a set of carefully selecte...

This paper describes an affinity graph based approach to multi-document summarization. We incorporate a diffusion process to acquire semantic relationships between sentences, and then compute information richness of sentences by a graph rank algorithm on differentiated intra-document links and inter-document links between sentences. A greedy algorithm is employed to impose diversity penalty on ...

We present an approach for extractive single-document summarization. Our approach is based on a weighted graphical representation of documents obtained by topic modeling. We optimize importance, coherence and non-redundancy simultaneously using ILP. We compare ROUGE scores of our system with state-of-the-art results on scientific articles from PLOS Medicine and on DUC 2002 data. Human judges ev...

Numerous NLP tasks rely on clustering or community detection algorithms. For many of these tasks, the solutions are disjoint, and the relevant evaluation metrics assume nonoverlapping clusters. In contrast, the relatively recent task of abstractive community detection (ACD) results in overlapping clusters of sentences. ACD is a sub-task of an abstractive summarization system and represents a tw...

We participated in the iUnit ranking subtask and the iUnit summarization subtask of the NTCIR-12 MobileClick for the Japanese and English languages. Our strategy is based on link analysis on an iUnit-page bipartite graph. First, we constructed an iUnit-page bipartite graph considering the entailment relationship between the iUnits and the pages. Then, we ranked the iUnits by their scores based ...

Given a large, real graph, how can we generate a synthetic graph that matches its properties, i.e., it has similar degree distribution, similar (small) diameter, similar spectrum, etc? We propose to use “Kronecker graphs”, which naturally obey all of the above properties. We present a fast linear time algorithm for fitting the Kronecker graph generation model to real networks. Experiments on la...

We introduce GoWvis1, an interactive web application that represents any piece of text inputted by the user as a graph-ofwords and leverages graph degeneracy and community detection to generate an extractive summary (keyphrases and sentences) of the inputted text in an unsupervised fashion. The entire analysis can be fully customized via the tuning of many text preprocessing, graph building, an...

We introduce GoWvis1, an interactive web application that represents any piece of text inputted by the user as a graph-ofwords and leverages graph degeneracy and community detection to generate an extractive summary (keyphrases and paragraph) of the inputted text in an unsupervised fashion. The entire analysis can be fully customized via the tuning of many text preprocessing, graph building, an...

Text summarization is an important field in the area of natural language processing and text mining. This paper proposes an extraction-based model which uses graphbased and information theoretic concepts for multidocument summarization. Our method constructs a directed weighted graph from the original text by adding a vertex for each sentence, and compute a weighted edge between sentences which...