Paper Info
Title
ExtremeReader: An interactive explorer for customizable and explainable review summarization
Abstract
Building summarization systems have become a necessity due to the extensive volume and growth of online reviews. Despite extensive research on this topic, existing summarization systems generally fall short on two aspects. First, existing techniques generate static summaries which cannot be tailored to specific user needs. Second, most existing systems generate extractive summaries which selects only certain salient aspects from the summaries. Hence, they do not completely depict the overall opinion of the reviews. In this paper, we demonstrate a novel summarization system, ExtremeReader, that overcomes the limitations of existing summarization systems described above. ExtremeReader allows summaries to be tailored and explored interactively so that users can quickly find the desired information. In addition, ExtremeReader generates abstractive summaries with an underlying structure that helps users understand, explore, and seek explanations to the generated summaries.
Year
DOI
Venue
2020
10.1145/3366424.3383535
WWW '20: The Web Conference 2020 Taipei Taiwan April, 2020
DocType
ISBN
Citations 
Conference
978-1-4503-7024-0
0
PageRank 
References 
Authors
0.34
0
9
Name
Order
Citations
PageRank
Xiaolan Wang16812.87
Yoshihiko Suhara23912.01
Natalie Nuno300.34
Yuliang Li45416.90
Jinfeng Li522.41
Nofar Carmeli664.84
Stefanos Angelidis700.68
Eser Kandogann800.34
WC Tan92529198.85