Files in this item

FilesDescriptionFormat

application/pdf

application/pdfopinosis.pdf (644kB)
opinosis_paperPDF

Description

Title:Opinosis: A Graph Based Approach to Abstractive Summarization of Highly Redundant Opinions
Author(s):Ganesan, Kavita; Zhai, ChengXiang; Han, Jiawei
Subject(s):abstractive summarization
opinion summarization
text summarization
graph mining
graph summarization
Abstract:We present a novel graph-based summarization framework (Opinosis) that generates concise abstractive summaries of highly redundant opinions. Evaluation results on summarizing user reviews show that Opinosis summaries have better agreement with human summaries compared to the baseline extractive method. The summaries are readable, reasonably well-formed and are informative enough to convey the major opinions.
Issue Date:2010
Publisher:COLING 2010
Citation Info:Kavita Ganesan, ChengXiang Zhai, Jiawei Han, "Opinosis: A Graph Based Approach to Abstractive Summarization of Highly Redundant Opinions", Proceedings of the 23rd International Conference on Computational Linguistics (COLING 2010), Beijing, China, 2010
Genre:Conference Paper / Presentation
Type:Text
Language:English
URI:http://hdl.handle.net/2142/16555
Publication Status:published or submitted for publication
Peer Reviewed:is peer reviewed
Date Available in IDEALS:2010-07-08


This item appears in the following Collection(s)

Item Statistics