Abstract
The rapid development of the Internet leads to the rapid growth of network information, we call it information explosion. The Internet is full of information, and it is difficult for users to find this information and useful knowledge of the ocean. The Web has become the world's largest information repository, and there is an urgent need for efficient access to the valuable knowledge of vast amounts of web information. The purpose of this paper is to study the process and algorithm analysis of text mining system based on artificial intelligence. This paper presents an algorithm of document feature acquisition based on genetic algorithm. Selecting suitable features is an important task in specific text classification and information retrieval. Finding appropriate feature vectors to represent the text will undoubtedly help with subsequent sorting and grouping. Based on the genetic algorithm of variable length chromosome, this paper improves the crossover, mutation and selection operations, and proposes an algorithm to obtain text feature vectors. This method has a wide range of applications and good results.
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