Abstract
The existing Fuzzy C-means (FCM) clustering algorithm can only cluster the web documents samples with a pre-known cluster number c which is impossible in practical situations. A new method based on fuzzy c-means algorithm for search results clustering is proposed in this paper. The new clustering method combines FCM algorithm with Affinity Propagation (AP) algotithm to find the optimal c for search results. It is proved that the new method has a better performance in accuracy than traditional method in search results clustering.
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Wang, F., Lu, Y., Zhang, F., Sun, S. (2013). A New Method Based on Fuzzy C-Means Algorithm for Search Results Clustering. In: Yuan, Y., Wu, X., Lu, Y. (eds) Trustworthy Computing and Services. ISCTCS 2012. Communications in Computer and Information Science, vol 320. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35795-4_33
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DOI: https://doi.org/10.1007/978-3-642-35795-4_33
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-35794-7
Online ISBN: 978-3-642-35795-4
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