A Summarization System for Scientific Documents
Shai Erera
Michal Shmueli-Scheuer
Guy Feigenblat
O. Nakash
O. Boni
Haggai Roitman
Doron Cohen
Bar Weiner
Y. Mass
Or Rivlin
Guy Lev
Achiya Jerbi
Jonathan Herzig
Yufang Hou
Charles Jochim
Martin Gleize
Francesca Bonin
D. Konopnicki

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.
View on arXivComments on this paper