Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Fuzzy logic methods in recommender systems
Fuzzy Sets and Systems - Theme: Multicriteria decision
Intelligent e-government services with personalized recommendation techniques: Research Articles
International Journal of Intelligent Systems
Advances in Fuzzy Clustering and its Applications
Advances in Fuzzy Clustering and its Applications
A Nonlinear Mapping for Data Structure Analysis
IEEE Transactions on Computers
Model-based collaborative filtering as a defense against profile injection attacks
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Government-to-business personalized e-services using semantic-enhanced recommender system
EGOVIS'11 Proceedings of the Second international conference on Electronic government and the information systems perspective
Design of a P2P content recommendation system using affinity networks
Computer Communications
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eDemocracy aims to increase participation of citizens in democratic processes through the use of information and communication technologies. In this paper, an architecture of recommender systems for eElections using fuzzy clustering methods is proposed. The objective is to assist voters in making decisions by providing information about candidates close to the voters preferences and tendencies. The use of recommender systems for eGovernment is a research topic used to reduce information overload, which could help to improve democratic processes.