Title : 
Fax clustering algorithm based on adaptive ant colony optimize
         
        
            Author : 
Hongtao, Yu ; Qing, Li ; Ying, Hou
         
        
            Author_Institution : 
Nat. Digital Switching Syst. Eng. & Technol. Res. Center, Zhengzhou, China
         
        
        
        
            Abstract : 
The fax clustering is that the same or similar faxes will be clustered into one group in mass faxes. In order to improve accuracy of clustering, a fax clustering algorithm based on adaptive ant colony optimization was proposed in this paper. The algorithm simulates ant feeding theory, and improves the coefficient of pheromone updating, and avoids falling into local optimum. The experimental results show that the algorithm has good robustness. The effect of clustering is improved obviously.
         
        
            Keywords : 
optimisation; pattern clustering; adaptive ant colony optimize; ant feeding theory; fax clustering algorithm; Algorithm design and analysis; Classification algorithms; Clustering algorithms; Facsimile; Heuristic algorithms; Robustness; Signal processing algorithms; ants colony; fax clustering; pheromone; robustness;
         
        
        
        
            Conference_Titel : 
Signal Processing Systems (ICSPS), 2010 2nd International Conference on
         
        
            Conference_Location : 
Dalian
         
        
            Print_ISBN : 
978-1-4244-6892-8
         
        
            Electronic_ISBN : 
978-1-4244-6893-5
         
        
        
            DOI : 
10.1109/ICSPS.2010.5555784