The traditional retrieval method cannot respond to the influence of the change in the portal website’s information characteristics, resulting in low efficiency. In this regard, a fast information retrieval method based on a chaotic genetic algorithm is proposed. According to the relevant theory of association rules, the correlation between information data of dynamic portal websites is calculated; different portal website information is retrieved based on the Markov model output; a chaotic genetic algorithm is used to fuse different portal website information. The information data constructs a decision tree for rapid retrieval of portal information, uses the vector form to express the characteristics of portal information, and finally realizes the rapid retrieval of portal information. The experimental results show that the designed method takes up to 15 ms when the sample complexity is high, which shows that the designed method has high efficiency and is of great significance in practical applications.