Mongolian information retrieval method based on LDA model

摘要

A new method based on Latent Dirichlet Allocation (LDA) is proposed to retrieval information in Mongolian. Semantic information is also considered by Mongolian documents when consider relationship between keywords and retrieval documents. This method models Mongolian documents with LDA, parameters are estimated with Gibbs sampling and probability of word is represented, it can mine the hidden relationship between the different topics and the words from documents, get the topic distribution and compute the similarity of keywords topics. Finally, return to the most relevant documents with topics. Experimental results show that the method has a higher performance in topic semantic compared with vector space model and Language model.