Document summarization via self-present sentence relevance model

Xiaodong LI, Shanfeng ZHU*, Haoran XIE, Qing LI

*Corresponding author for this work

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review

7 Citations (Scopus)


Automatic document summarization is always attractive to computer science researchers. A novel approach is proposed to address this topic and mainly focuses on the summarization of plain documents. Conventional summarization methods do not fully use the inter-sentence relevance that is not preserved during the processing. In contrast, to tackle the problem and incorporate the latent relations among sentences, our approach constructs relevance structures at sentence-level for plain documents and each sentence is scored with a significance value. Accordingly, important sentences "present" themselves automatically, and the summary paragraph is then generated by selecting top-k scored sentences. Convergence of the algorithm is proved, and experiment, which is conducted on two data sets (DUC 2006 and DUC 2007), shows that the proposed model gives convincing results.

Original languageEnglish
Title of host publicationDatabase Systems for Advanced Applications - 18th International Conference Proceedings
EditorsWeiyi MENG, Ling FENG, Stéphane BRESSAN, Werner WINIWARTER
Place of PublicationBerlin
PublisherSpringer Berlin Heidelberg
Number of pages15
ISBN (Electronic)9783642374500
ISBN (Print)9783642374494
Publication statusPublished - 2013
Externally publishedYes
EventThe 18th International Conference on Database Systems for Advanced Applications - Wuhan, China
Duration: 22 Apr 201325 Apr 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume7826 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


ConferenceThe 18th International Conference on Database Systems for Advanced Applications
Abbreviated titleDASFAA 2013
Internet address


  • Sentence relevance
  • Summarization


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