Unsupervised Topic Modeling Revolutionizes Document Clustering, Unlocking Hidden Semantic Connections.
The article introduces a new method called DPMFS to help select the right number of hidden variables in document clustering. By using a backward elimination approach, the method can identify which variables to remove for better performance. The results show that this algorithm can optimize the number of hidden variables, leading to improved clustering accuracy.
