Text Modeling Based on the Analysis of Categorical Words

Recently the most essential research in machine learning is to discover correct topics from large scale of electronic documents, and many studies about text modeling have been made in natural language process with the environment of big data. This paper discusses a fundamental way for people to form words while talking and describing ideas, the document is considered as words convergence and a new method for text modeling based on the relational analysis about verbs, nouns, and modifiers is proposed. Additionally the paper introduces a new algorithm for estimating parameters in the generative probabilities of the model, which can alleviate the process about statistics-based text analysis from computational complexity. Experimental results show that the method improves the quality for learning a document.