Study on Classification of News Topic Based on LDA Model
Tan Cheng-fan · Computer Knowledge and Technology · 2014
The LDA model is applied to the classification of news topic on the website because of its no classification or unclear classification. Firstly, news dataset is modeled by LDA modeling, the optimal number of topic is chosen according to Bias standard method, and get the topic probability distribution of dataset by using Gibbs sampling to calculate the model parameters; and then similarity matrix is obtained based on the semantic similarity between documents by computing JS distance; finally, the incremental clustering algorithm is used to cluster news document, and the topic is divided into a number of different structure of the sub topic. The experimental results show that this method can realize the division of news topic effectively.