Data mining through fuzzy social network analysis

被引：32

作者：

Nair, Premchand S. ^{[1
]}

Sarasamma, Suseela T. ^{[2
]}

机构：

[1] Creighton Univ, Dept Comp Sci, Omaha, NE 68178 USA

[2] Northrop Grumman Mission Syst, Bellevue, NE 68005 USA

来源：

NAFIPS 2007 - 2007 ANNUAL MEETING OF THE NORTH AMERICAN FUZZY INFORMATION PROCESSING SOCIETY | 2007年

关键词：

D O I：

10.1109/NAFIPS.2007.383846

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, fuzzy theory has been applied to Social Network Analysis (SNA). Social Network Analysis models meaningful relations that Exist between entities as graph. These entities may be people, events, organizations, symbols in text, sounds in verbalizations, nations of the world and so on. However, the fuzzy graph can be very huge and thus the ability to arrive at meaningful conclusions in a timely fashion may be quite difficult. With this in mind, a method to consolidate the information content of the fuzzy graph is proposed. Since none of the existing fuzzy binary operations meet the requirements, a new fuzzy binary operation called consolidation operation is also introduced.

引用

页码：251 / +

页数：2

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