A High Performance Modified K-Means Algorithm for Dynamic Data Clustering in Multi-core CPUs Based Environments

Author(s):  
Giuliano Laccetti ◽  
Marco Lapegna ◽  
Valeria Mele ◽  
Diego Romano
2017 ◽  
Vol 9 (1) ◽  
pp. 52-63 ◽  
Author(s):  
K S Shailesh ◽  
Suresh Pachigolla Venkata

Dividing the web site page content or web portal page into logical chunks is one of the prominent methods for better management of web site content and for improving web site's performance. While this works well for public web page scenarios, personalized pages have challenges with dynamic data, data caching, privacy and security concerns which pose challenges in creating and caching content chunks. Web portals has huge dependence on personalized data. In this paper the authors have introduced a novel concept called “personalized content chunk” and “personalized content spot” that can be used for segregating and efficiently managing the personalized web scenarios. The authors' experiments show that performance can be improved by 30% due to the personalized content chunk framework.


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