Affiliation:
1. University of Zanjan, Zanjan, Iran
2. Iran University of Science and Technology, Tehran, Iran
3. Department of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran
Abstract
As a way of simplifying, size reducing and making the structure of each social network be comprehensible, blockmodeling consists of two major, essential components: partitioning of actors to equivalent classes, called positions, and clarifying relations between and within positions. While actor partitioning in conventional blockmodeling is performed by several equivalence definitions, generalized blockmodeling, searches, locally, the best partition vector that best satisfies a predetermined structure. The need for known predefined structure and using a local search procedure, makes generalized blockmodeling be restricted. In this paper, the authors formulate blockmodel problem and employ a genetic algorithm for to search for the best partition vector fitting into original relational data in terms of the known indices. In addition, during multiple samples and situations such as dichotomous, signed, ordinal and interval valued, and multiple relations, the quality of results shows better fitness than classic and generalized blockmodeling.
Subject
Decision Sciences (miscellaneous),Computational Mathematics,Computational Theory and Mathematics,Control and Optimization,Computer Science Applications,Modeling and Simulation,Statistics and Probability
Reference44 articles.
1. Mixed membership stochastic blockmodels.;E. M.Airoldi;Journal of Machine Learning Research,2008
2. Building stochastic blockmodels
3. Swarm Intelligence for Automatic Video Image Contrast Adjustment
4. An algorithm for clustering relational data with applications to social network analysis and comparison with multidimensional scaling
5. A variable neighborhood search method for a two-mode blockmodeling problem in social network analysis.;M.Brusco;New Scientist,2013
Cited by
5 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献