Research on the Key Technology of Web Data Extraction and Mining Based on the Probability Distribution

Abstract

In the development of internet technology innovation, the quantity of big data information continues to rise, showing the characteristics of dynamic, heterogeneous, massive, and so on. How to explore valuable and potential knowledge from the network system is the main topic of research and scholars. Based on the understanding of web data extraction and web mining technology, this paper makes a systematic study of web text mining, proposes the most commonly used hidden Markov model in probability distribution, and constructs the corresponding text mining method. The hidden Markov model is a statistical model, which is mainly used to represent a Markov process with unknown parameters. The difficulty in practical application lies in how to define the hidden parameters of the process from observable parameters and then use these parameters to conduct in-depth research. Finally, the practical results show that the hidden Markov model can not only obtain the information of different regions but also deeply analyze the data set, which proves the feasibility of this research technology.