@inproceedings{eebc10d919df4341bf6f1846271deb58,
title = "Modified affinity propagation clustering",
abstract = "Affinity propagation clustering is an efficient clustering technique that does not require prior knowledge of the number of clusters. However, it sets the input preferences without considering data set distribution and competition in the former iteration is ignored when updating messages passing between data points. This paper presents a modified affinity propagation algorithm. Firstly, preference for each data point to serve as an exemplar is computed self-adaptively based on data set distribution; then encouragement and chastisement mechanism is introduced for updating message of availability. Experimental results on standard data sets and synthetic data sets demonstrate feasibility and effectiveness of the proposed algorithm.",
keywords = "Affinity Propagation, Data set Distribution, Encouragement and Chastisement, Preference",
author = "Jing Zhang and Mingyi He and Yuchao Dai",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2nd IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014 ; Conference date: 09-07-2014 Through 13-07-2014",
year = "2014",
month = sep,
day = "3",
doi = "10.1109/ChinaSIP.2014.6889294",
language = "English",
series = "2014 IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "505--509",
booktitle = "2014 IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014 - Proceedings",
address = "United States",
}