Network Analysis and Knowledge Discovery Through DNA Computing

2006 ◽  
Author(s):  
Anthony Macula
Author(s):  
Luca Cagliero ◽  
Alessandro Fiori

This Chapter overviews most recent data mining approaches proposed in the context of social network analysis. In particular, it aims at classifying the proposed approaches based on both the adopted mining strategies and their suitability for supporting knowledge discovery in a dynamic context. To provide a thorough insight into the proposed approaches, main work issues and prospects in dynamic social network analysis are also outlined.


Author(s):  
Manish Kumar

Social Networks are nodes consisting of people, groups and organizations growing dynamically. The growth is horizontal as well as vertical in terms of size and number. Social network analysis has gained success due to online social networking and sharing sites. The accessibility of online social sites such as MySpace, Facebook, Twitter, Hi5, Friendster, SkyRock and Beb offer sharing and maintaining large amount of different data. Social network analysis is focused on mining such data i.e. generating pattern of people’s interaction. The analysis involves the knowledge discovery that helps the sites as well as users in terms of usage and business goals respectively. Further it is desired that the process must be privacy preserving. This chapter describes the various mining techniques applicable on social networks data.


2004 ◽  
Vol 171 (4S) ◽  
pp. 502-503
Author(s):  
Mohamed A. Gomha ◽  
Khaled Z. Sheir ◽  
Saeed Showky ◽  
Khaled Madbouly ◽  
Emad Elsobky ◽  
...  

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