TY - GEN
T1 - Document summarization via self-present sentence relevance model
AU - Li, Xiaodong
AU - Zhu, Shanfeng
AU - Xie, Haoran
AU - Li, Qing
PY - 2013/12/1
Y1 - 2013/12/1
N2 - 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.
AB - 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.
KW - Sentence relevance
KW - Summarization
UR - http://www.scopus.com/inward/record.url?scp=84892899366&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-37450-0_24
DO - 10.1007/978-3-642-37450-0_24
M3 - Conference article published in proceeding or book
AN - SCOPUS:84892899366
SN - 9783642374494
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 309
EP - 323
BT - Database Systems for Advanced Applications - 18th International Conference, DASFAA 2013, Proceedings
T2 - 18th International Conference on Database Systems for Advanced Applications, DASFAA 2013
Y2 - 22 April 2013 through 25 April 2013
ER -