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.
Highlights
In recent years, the boom of network technology has ushered in the information age [1,2]
The findings show that the improved KNN algorithm is feasible for storage and allocation of English teaching resources; it has high operation efficiency and reliable classification results
term frequency-inverse document frequency (TF-IDF) has a better effect than other weight algorithms, there are still gap that it has not considered whether the feature items TZ3 are evenly distributed in all resources or concentrate in one resource
Summary
The boom of network technology has ushered in the information age [1,2]. The schools usually classified educational resources manually since the Internet was not popular. Those with professional knowledge were allowed to. Manual allocation is inefficient and inaccurate as the number of resources continues to increase [11] In this case, how to effectively store and classify the teaching resources in the network is a staggering problem that needs to be solved urgently [12]. The findings show that the improved KNN algorithm is feasible for storage and allocation of English teaching resources; it has high operation efficiency and reliable classification results
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