Online English Intelligent Question Answering System Based on K-Means Algorithm

In the current information age, people's demand for information acquisition is becoming increasingly urgent. However, traditional search engines often face problems such as high information content and uneven quality, making it difficult to meet users’ needs. Therefore, how to improve the credibility and pertinence of search results has become an urgent problem to be solved. Therefore, this paper proposes a new wireless web crawler strategy, which aims to provide users with more accurate and efficient information search services. This paper aims to explore a wireless web crawler strategy based on K-means algorithm. From the perspective of users, this article utilizes intelligent question answering systems and specific dictionary content and non keyword retrieval techniques to achieve the search and generation of target information. Afterwards, this article conducted functional testing on the system, and the test results showed that the overall similarity and accuracy of the system were high, indicating that the system performed well in practical application scenarios. The fusion application of online English intelligent question answering system based on K-means algorithm has made some research findings. Here are some related research findings: The K-means algorithm can effectively classify user questions and generate corresponding answers. By conducting cluster analysis on a large number of Q&A datasets, the system can automatically learn the features and patterns of the problem, and classify the problem into groups that should provide the same or similar answers based on similarity.