Latent Topic Discovery from Text Based on Adaptive Clustering Algorithm
Tingting He · Journal of Zhengzhou University · 2007
A novel approach to discovering topics and determining the number of latent topics K in a text automatically is proposed.By adopting K-means clustering algorithm as well as a clustering analysis algorithm based on self-defined discriminative function,the number of different latent topics in a text is captured and the diverse topics are found accordingly.Experimental results demonstrate that the proposed approach can deal with various texts with free writing style and flexible topic distribution effectively.