Title
A Summarization System for Scientific Documents
Abstract
We present a novel system providing summaries for Computer Science publications. Through a qualitative user study, we identified the most valuable scenarios for discovery, exploration and understanding of scientific documents. Based on these findings, we built a system that retrieves and summarizes scientific documents for a given information need, either in form of a free-text query or by choosing categorized values such as scientific tasks, datasets and more. Our system ingested 270,000 papers, and its summarization module aims to generate concise yet detailed summaries. We validated our approach with human experts.
Year
DOI
Venue
2019
10.18653/v1/D19-3036
EMNLP/IJCNLP (3)
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
0
18
Name
Order
Citations
PageRank
Shai Erera1121.82
Michal Shmueli-Scheuer28916.11
Guy Feigenblat34712.99
Ora Peled Nakash400.34
Odellia Boni572.58
Haggai Roitman631432.07
Doron Cohen716316.38
Bar Weiner800.34
Yosi Mass957460.91
Or Rivlin1000.34
Guy Lev11743.89
Achiya Jerbi1200.34
Jonathan Herzig13479.65
Yufang Hou143610.35
Charles Jochim15405.43
Martin Gleize1675.67
Francesca Bonin176812.95
David Konopnicki18377144.72