Title
Fuzzy swarm diversity hybrid model for text summarization
Abstract
High quality summary is the target and challenge for any automatic text summarization. In this paper, we introduce a different hybrid model for automatic text summarization problem. We exploit strengths of different techniques in building our model: we use diversity-based method to filter similar sentences and select the most diverse ones, differentiate between the more important and less important features using the swarm-based method and use fuzzy logic to make the risks, uncertainty, ambiguity and imprecise values of the text features weights flexibly tolerated. The diversity-based method focuses to reduce redundancy problems and the other two techniques concentrate on the scoring mechanism of the sentences. We presented the proposed model in two forms. In the first form of the model, diversity measures dominate the behavior of the model. In the second form, the diversity constraint is no longer imposed on the model behavior. That means the diversity-based method works same as fuzzy swarm-based method. The results showed that the proposed model in the second form performs better than the first form, the swarm model, the fuzzy swarm method and the benchmark methods. Over results show that combination of diversity measures, swarm techniques and fuzzy logic can generate good summary containing the most important parts in the document.
Year
DOI
Venue
2010
10.1016/j.ipm.2010.03.004
Inf. Process. Manage.
Keywords
Field
DocType
fuzzy swarm diversity,summarization,fuzzy swarm-based method,text summarization,particle swarm optimization,diversity,feature,different hybrid model,fuzzy logic,diversity-based method,model behavior,fuzzy swarm method,swarm model,diversity measure,benchmark method
Particle swarm optimization,Automatic summarization,Data mining,Swarm behaviour,Computer science,Fuzzy logic,Swarm intelligence,Exploit,Redundancy (engineering),Artificial intelligence,Ambiguity
Journal
Volume
Issue
ISSN
46
5
Information Processing and Management
Citations 
PageRank 
References 
20
0.76
26
Authors
3
Name
Order
Citations
PageRank
Mohammed Salem Binwahlan1674.70
Naomie Salim242448.23
Ladda Suanmali3392.80