.png){kind=icon}
Return
PSG: a two-layer graph model for document summarization
.png){kind=icon}
PRE
AI
DOI：10.1007/s11704-013-2292-2.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Graph model has been widely applied in document summarization by using sentence as the graph node, and the similarity between sentences as the edge. In this paper, a novel graph model for document summarization is presented, that not only sentences relevance but also phrases relevance information included in sentences are utilized. In a word, we construct a phrase-sentence two-layer graph structure model (PSG) to summarize document(s). We use this model for generic document summarization and query-focused summarization. The experimental results show that our model greatly outperforms existing work.
Keywords:
relationship graph
Markov random walk
document summarization
Journal
IF:
4.6
Papers:
1.6K
Citations:
2.8K
Organization
No organization information available
Cited Papers
ShareSaveShareSaveShareSaveMechanical characterization of neural electrodes based on PDMS-parylene C-PDMS sandwiched system
PREAI
ShareSaveShareSaveQuality of service evaluation based on network slicing for software-defined 5G systems.png)
TecnoLógicas
OAAI
TecnoLógicasIF0
OAAIShareSave
View more