Storage and Allocation of English Teaching Resources Based on k-Nearest Neighbor Algorithm

Abstract

The boom of Internet technology gives a boost to the informatization of education in China. Internet resources serve as a new carrier of knowledge, offering teachers and students an alternative to books. However, the exponential growth of Internet resources has greatly complicated the storage and allocation of resources. This paper attempts to fully utilize English teaching resources through effective resource management and allocation. Specifically, the features of English teaching resources were analyzed, and then the term frequency-inverse document frequency (TF-IDF) weight method and k-nearest neighbor (kNN) algorithm were improved to make resource allocation more efficient and effective. The improved methods were then verified through a case analysis. The results show that the improved kNN provides a feasible way to allocate English teaching resources. The research findings provide reference to the storage and allocation of teaching resources.