Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/78393
Title: Timestamped graphs: Evolutionary models of text for multi-document summarization
Authors: Lin, Z.
Kan, M.-Y. 
Issue Date: 2007
Source: Lin, Z.,Kan, M.-Y. (2007). Timestamped graphs: Evolutionary models of text for multi-document summarization. HLT-NAACL 2007 - TextGraphs 2007: Graph-Based Algorithms for Natural Language Processing, Proceedings of the Workshop : 25-32. ScholarBank@NUS Repository.
Abstract: Current graph-based approaches to automatic text summarization, such as LexRank and TextRank, assume a static graph which does not model how the input texts emerge. A suitable evolutionary text graph model may impart a better understanding of the texts and improve the summarization process. We propose a timestamped graph (TSG) model that is motivated by human writing and reading processes, and show how text units in this model emerge over time. In our model, the graphs used by LexRank and TextRank are specific instances of our timestamped graph with particular parameter settings. We apply timestamped graphs on the standard DUC multi-document text summarization task and achieve comparable results to the state of the art.
Source Title: HLT-NAACL 2007 - TextGraphs 2007: Graph-Based Algorithms for Natural Language Processing, Proceedings of the Workshop
URI: http://scholarbank.nus.edu.sg/handle/10635/78393
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

Page view(s)

15
checked on Jan 20, 2018

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.