Patent Document ID: 20140129510
Application ID: 14153257
Patent Status: 0

Claim One:
1. A parameter inference method based on a Latent Dirichlet Allocation model, comprising: calculating a Latent Dirichlet Allocation model according to a preset initial first hyperparameter, a preset initial second hyperparameter, a preset initial number of topics, a preset initial global count matrix of documents and topics, and a preset initial global count matrix of topics and words, to obtain a probability distribution between documents and topics and a probability distribution between topics and words; obtaining, by using an expectation maximization algorithm, a first hyperparameter, a second hyperparameter, and the number of topics that maximize log likelihood functions of the probability distributions; and determining whether the first hyperparameter, the second hyperparameter, and the number of topics converge, and when the first hyperparameter and the second hyperparameter do not converge, putting the first hyperparameter, the second hyperparameter, and the number of topics into the Latent Dirichlet Allocation model for calculation until an optimal first hyperparameter, an optimal second hyperparameter, and an optimal number of topics that maximize the log likelihood functions of the probability distributions converge, and outputting the probability distributions, the optimal first hyperparameter, the optimal second hyperparameter, and the optimal number of topics that are eventually obtained.