Abstract
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.
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References
Vozalis, E., Margaritis, K.: Analysis of Recommender Systems’ Algorithms. In: The Sixth Hellenic European Conference on Computer Mathematics and its Applications (HERCMA 2003), Athens, Greece (2003)
Guo, X., Lu, J.: Intelligent E-Government Services with Personalized Recommendation Techniques. International Journal of Intelligent Systems 22, 401–417 (2007)
Sarwar, B., Karypis, G., Konstan, J.: Item-based Collaborative Filtering Recommendation Algorithms. In: 10th International World Wide Web Conference, Hong Kong, pp. 285–295 (2001)
Yager, R.: Fuzzy Logic Methods in Recommender Systems. Fuzzy Sets and Systems 136, 133–149 (2003)
Mobashe, R., Burke, R., Sandvig, J.: Model-Based Collaborative Filtering as a Defense Against Profile Injection Attacks. In: Proceedings of the 21st National Conference on Artificial Intelligence (AAAI’06), Boston, Massachusetts (2006)
Zadeh, L.: Fuzzy Sets. Department of Electrical Engineering and Electronics Research Laboratory, Berkeley, California (1965)
Bezdec, J.C.: Pattern Recognition with Fuzzy Objective Function Algorithms. Plenum Press, New York (1981)
Sammon, J.W.: A Nonlinear mapping for Data Structure Analysis. IEEE Transactions on Computers C-18(5) (1969)
Meier, A.: eDemocracy & eGovernment. Springer, Berlin (2009)
Valente de Oliveira, J., Witold, P.: Advances in Fuzzy Clustering and its Aplications. Wiley, West Sussex (2007)
Smartvote, http://www.smartvote.ch/
ACE Project, http://aceproject.org/ace-en/topics/pc/pca/pca01/pca01a
European Commission, http://ec.europa.eu/information_society/activities/egovernment/index_en.htm
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Terán, L., Meier, A. (2010). A Fuzzy Recommender System for eElections. In: Andersen, K.N., Francesconi, E., Grönlund, Å., van Engers, T.M. (eds) Electronic Government and the Information Systems Perspective. EGOVIS 2010. Lecture Notes in Computer Science, vol 6267. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15172-9_6
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DOI: https://doi.org/10.1007/978-3-642-15172-9_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15171-2
Online ISBN: 978-3-642-15172-9
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