Computing and applying trust in web-based social networks
Computing and applying trust in web-based social networks
Ant-Based Clustering and Topographic Mapping
Artificial Life
Community detection in social networks with genetic algorithms
Proceedings of the 10th annual conference on Genetic and evolutionary computation
SYNASC '08 Proceedings of the 2008 10th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing
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ECAL'07 Proceedings of the 9th European conference on Advances in artificial life
PSO aided k-means clustering: introducing connectivity in k-means
Proceedings of the 13th annual conference on Genetic and evolutionary computation
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This paper is concerned with a problem in information organization and retrieval within Web communities. Most work in this domain is focused on reputation-based systems which exploit the experience gathered by previous users in order to evaluate resources at the community level. The current research focuses on a slightly different approach: a personalized evaluation system whose goal is to build a flexible and easy way to manage resources in a personalized manner. The functionality of such a model comes from local trust metrics which propagate the trust to a limited level into the system and, finally, lead to the appearance of minorities sharing some similar features/preferences. A modified PSO procedure is designed in order to analyze such a system and, in conjunction with a simple agglomerative clustering algorithm, identify homogenous groups of users.