Construction of College English Teaching Information Resource Integration Model Based on Fuzzy Clustering Algorithm

Abstract

The existing college English teaching information resource integration methods have problems of low recall rate, low accuracy rate, and long integration time. Therefore, this paper constructs a college English teaching information resource integration model based on fuzzy clustering algorithm. The ant colony algorithm is used to optimize the topic crawler, the optimized topic crawler is used to collect the college English teaching information resources in the mixed teaching mode, and the weight and naive Bayes algorithm are combined to classify the collected resources. According to the results of resource classification, fuzzy clustering algorithm is used to construct the integration model of college English teaching information resources. The experimental results show that the recall rate of the proposed model is more than 95%, the accuracy rate is more than 94%, and the average resource integration time is only 0.71 s, indicating that the model has relatively reliable performance.