A Text Mining Model Based on Improved Density Clustering Algorithm

作者：Chen Qi^*; Lu Jianfeng; Zhang Hao

来源：4th IEEE International Conference on Electronics Information and Emergency Communication (ICEIEC), 2013-11-15 to 2013-11-17.

• clustering algorithm
• text mining
• density clustering

The clustering algorithm based on density is widely used on text mining model, for example the DBSCAN(density-based spatial clustering of application with noise) algorithm. DBSCAN algorithm is sensitive in choose of parameters, it is hard to find suitable parameters. In this paper a method based on k-means algorithm is introduced to estimate the E neighborhood and minpts. Finally an example is given to show the effectiveness of this algorithm.

• 出版日期2014
• 单位同济大学