Text Summarization Using FrameNet-Based Semantic Graph Model
Joint Authors
Wang, Cong
Han, Xu
Lv, Tao
Hu, Zhirui
Wang, Xinyan
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-11-27
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Text summarization is to generate a condensed version of the original document.
The major issues for text summarization are eliminating redundant information, identifying important difference among documents, and recovering the informative content.
This paper proposes a Semantic Graph Model which exploits the semantic information of sentence using FSGM.
FSGM treats sentences as vertexes while the semantic relationship as the edges.
It uses FrameNet and word embedding to calculate the similarity of sentences.
This method assigns weight to both sentence nodes and edges.
After all, it proposes an improved method to rank these sentences, considering both internal and external information.
The experimental results show that the applicability of the model to summarize text is feasible and effective.
American Psychological Association (APA)
Han, Xu& Lv, Tao& Hu, Zhirui& Wang, Xinyan& Wang, Cong. 2016. Text Summarization Using FrameNet-Based Semantic Graph Model. Scientific Programming،Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1118268
Modern Language Association (MLA)
Han, Xu…[et al.]. Text Summarization Using FrameNet-Based Semantic Graph Model. Scientific Programming No. 2016 (2016), pp.1-10.
https://search.emarefa.net/detail/BIM-1118268
American Medical Association (AMA)
Han, Xu& Lv, Tao& Hu, Zhirui& Wang, Xinyan& Wang, Cong. Text Summarization Using FrameNet-Based Semantic Graph Model. Scientific Programming. 2016. Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1118268
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1118268