Document Clustering by Fuzzy C-Mean Algorithm

摘要：

Clustering documents enable the user to have a good overall view of the information contained in the documents.Most classical clustering algorithms assign each data to exactly one cluster,thus forming a crisp partition of the given data,but fuzzy clustering allows for degrees of membership,to which a data belongs to different clusters.In this system,documents are clustered by using fuzzy c-means (FCM) clustering algorithm.FCM clustering is one of well-know unsupervised clustering techniques.However FCM algorithm requires the user to pre-define the number of clusters and different values of clusters corresponds to different fuzzy partitions.So the validation of clustering result is needed.PBM index and F-measure are used for cluster validity.

关键词： Fuzzy c-mean algorithm Clulster Validity Document Clustering PBM index

作者: Thaung Thaung Win Lin Mon

作者单位: University of Computer Studies,Mandalay UCSM Yangon,Myanmar

会议类型: 国际会议

会议名称: The 2nd IEEE International Conference on Advanced Computer Control(第二届先进计算机控制国际会议 ICACC 2010)

会议地点: 沈阳

会议语种:英文

页码: 239-242

在线出版日期: 2010-03-27（万方平台首次上网日期，不代表论文的发表时间）