The traditional vertical search method only considers the content of the webpage, and the global master node is not enough, which will lead to premature convergence and fall into the local optimum, resulting in insufficient multi-dimensional search of resources. Therefore, this paper proposes a multidimensional resource vertical edge based on the calculation of English subject search method. This paper analyzes the architecture of search engine firstly and then introduces the multiaccess edge computing architecture. At last, it constructs the vertical search task computing model of multidimensional resources in English discipline. By associating and traversing the attributes of multidimensional resources of English discipline, the vertical search of attribute information is realized offline, and the vertical search method of multidimensional resources of English discipline based on edge calculation is designed. In order to verify the effectiveness of the proposed method, a comparative experiment is designed. Experimental results show that the method can improve the resource search ratio and recall ratio, and it can also effectively improve the search efficiency. For an English subject resource data of 50 MB, the calculation methods of edge multidimensional resource data search recall rate can reach 97% and multidimensional resource data search time consumption is only 39 ms. The experimental results show that the performance of English subject multidimensional resources vertical search is much better.

中文翻译：

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基于边缘计算的英语学科多维资源垂直搜索方法研究

传统的垂直搜索方法仅考虑网页的内容，而全局主节点不够用，这会导致过早收敛并陷入局部最优，导致资源的多维搜索不足。因此，本文基于英语主题搜索方法的计算，提出了多维资源垂直边缘。本文首先分析了搜索引擎的体系结构，然后介绍了多路访问边缘计算体系结构。最后，构建了英语学科多维资源的垂直搜索任务计算模型。通过关联和遍历英语学科多维资源的属性，可以离线实现属性信息的垂直搜索，设计了一种基于边缘计算的英语学科多维资源垂直搜索方法。为了验证所提方法的有效性，设计了一个对比实验。实验结果表明，该方法可以提高资源搜索率和查全率，也可以有效地提高搜索效率。对于50 MB的英语主题资源数据，边缘多维资源数据搜索召回率的计算方法可以达到97％，多维资源数据搜索的时间消耗仅为39 ms。实验结果表明，英语学科多维资源垂直搜索的性能要好得多。设计了一个对比实验。实验结果表明，该方法可以提高资源搜索率和查全率，也可以有效地提高搜索效率。对于50 MB的英语主题资源数据，边缘多维资源数据搜索召回率的计算方法可以达到97％，多维资源数据搜索的时间消耗仅为39 ms。实验结果表明，英语学科多维资源垂直搜索的性能要好得多。设计了一个对比实验。实验结果表明，该方法可以提高资源搜索率和查全率，也可以有效地提高搜索效率。对于50 MB的英语主题资源数据，边缘多维资源数据搜索召回率的计算方法可以达到97％，多维资源数据搜索的时间消耗仅为39 ms。实验结果表明，英语学科多维资源垂直搜索的性能要好得多。边缘多维资源数据搜索召回率的计算方法可以达到97％，多维资源数据搜索的时间消耗仅为39 ms。实验结果表明，英语学科多维资源垂直搜索的性能要好得多。边缘多维资源数据搜索召回率的计算方法可以达到97％，多维资源数据搜索的时间消耗仅为39 ms。实验结果表明，英语学科多维资源垂直搜索的性能要好得多。