Name
Abstract | ||
|---|---|---|
Automatic text summarization systems aim to make their created summaries closer to human summaries. The summary creation under
the condition of the redundancy and the summary length limitation is a challenge problem. The automatic text summarization
system which is built based on exploiting of the advantages of different techniques in form of an integrated model could produce
a good summary for the original document. In this paper, we introduced an integrated model for automatic text summarization
problem; we tried to exploit different techniques advantages in building of our model like advantage of diversity based method
which can filter the similar sentences and select the most diverse ones and advantage of the differentiation between the most
important features and less important using swarm based method. The experimental results showed that our model got the best
performance over all methods used in this study.
|
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-642-10684-2_24 | International Conference on Neural Information Processing |
Keywords | Field | DocType |
summary.,different technique,diversity,binary tree,swarm diversity,automatic text summarization system,human summary,challenge problem,automatic text summarization problem,mmi,integrated model,good summary,summarization,summary length limitation,summary creation,swarm,text summarization,different techniques advantage | Text graph,Multi-document summarization,Automatic summarization,Swarm behaviour,Computer science,Binary tree,Exploit,Redundancy (engineering),Artificial intelligence,Machine learning | Conference |
Volume | ISSN | Citations |
5864 | 0302-9743 | 2 |
PageRank | References | Authors |
0.36 | 15 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mohammed Salem Binwahlan | 1 | 67 | 4.70 |
| Naomie Salim | 2 | 424 | 48.23 |
| Ladda Suanmali | 3 | 39 | 2.80 |