Proceedings ArticleDOI
Data Mining Through Fuzzy Social Network Analysis
Premchand S. Nair,S.T. Sarasamma +1 more
- pp 251-255
TLDR
A method to consolidate the information content of the fuzzy graph is proposed and a new fuzzy binary operation called consolidation operation is also introduced.Abstract:
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.read more
Citations
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Journal ArticleDOI
Personalized Mobile Information Retrieval System
TL;DR: This study proposes methods of providing Personalized Mobile Information Retrieval System using NFC (Near Field Communication) Smartphone, which will be then used for Smartphone users and aims to verify its efficiency through a comparative analysis of existing studies.
Book ChapterDOI
A New Community Detection Algorithm Based on Fuzzy Measures
TL;DR: This work presents a modification of the well-known Louvain algorithm for crisp network that allows us to deal with fuzzy information in the network and incorporates to the classical Louvains the use of fuzzy measures for the nodes of the graph.
Journal ArticleDOI
A Novel Classification Method From the Perspective of Fuzzy Social Networks Based on Physical and Implicit Style Features of Data
TL;DR: A novel unified classification framework based on the proposed fuzzy social network and its dynamics about fuzzy influences of nodes that demonstrates distinctive superiority on five case studies where satisfactory classification certainly depends on both physical and implicit style features.
Journal ArticleDOI
Time-series prediction based on global fuzzy measure in social networks
TL;DR: Experimental results demonstrate that the fuzzy network has more superiority than the traditional network in describing the network evolution process and calculating the global fuzzy measure such as network density and centralization.
Journal ArticleDOI
A fuzzy social network centrality analysis model for interpersonal spatial relations
TL;DR: An evaluation index system, which contains fuzzy comentropy, fuzzy node degree, fuzzy condensation degrees, fuzzy cluster coefficient and fuzzy geographic concentration, is developed and proves that the proposed method can effectively reveal the essence of fuzzy centralities.
References
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Book
Social Network Analysis: Methods and Applications
TL;DR: This paper presents mathematical representation of social networks in the social and behavioral sciences through the lens of Dyadic and Triadic Interaction Models, which describes the relationships between actor and group measures and the structure of networks.
Journal ArticleDOI
Social Network Analysis: Methods and Applications.
TL;DR: This work characterizes networked structures in terms of nodes (individual actors, people, or things within the network) and the ties, edges, or links that connect them.
Book
Fuzzy Sets and Systems: Theory and Applications
Didier Dubois,Henri Prade +1 more
TL;DR: This book effectively constitutes a detailed annotated bibliography in quasitextbook style of the some thousand contributions deemed by Messrs. Dubois and Prade to belong to the area of fuzzy set theory and its applications or interactions in a wide spectrum of scientific disciplines.
Book
Fuzzy sets and systems
TL;DR: Fuzzy sets as mentioned in this paper are a class of classes in which there may be grades of membership intermediate between full membership and non-membership, i.e., a fuzzy set is characterized by a membership function which assigns to each object its grade of membership.
Book
Fuzzy Graphs and Fuzzy Hypergraphs
TL;DR: Fuzzy Subsets: Fuzzy Relations.- FuzzY Equivalence Relations.- Pattern Classification.- Similarity Relations.- References.- fuzzy Graphs: Paths and Connectedness.