Using Systematic Clustering to Improve Innovation and Enterprise Curriculum Keyword Selection in Search Engine Optimization

Zhixin Liu, Yaming Zheng, Dongliang Wang, Jiayi Chen, Jiawei Tian, Qilong Gong
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引用次数: 0

Abstract

Clustering is a typical unsupervised learning algorithm, which does not need to label the results. Try to find and summarize the specific pattern of a certain group, and divide the information to be classified into multiple different types according to their common characteristics. Innovation and enterprise course platform as an internet course platform, improving search engine ranking is very important for platform operation. The project incubation stage of innovation and enterprise course will be publicized on the platform in the form of crowdfunding, so as to get the attention of investors. Based on the comprehensive index evaluation method based on search engine optimization method, this paper puts forward an improvement scheme. Cluster analysis algorithm is added to the traditional method. This method establishes a perfect keyword optimization strategy management mechanism.
利用系统聚类改进搜索引擎优化中的创新与企业课程关键词选择
聚类是一种典型的无监督学习算法,它不需要对结果进行标记。试图发现和总结某一群体的具体模式,并根据其共同特征将待分类的信息分成多个不同的类型。创新与企业课程平台作为互联网课程平台,提高搜索引擎排名对平台运营至关重要。创新创业课程的项目孵化阶段将以众筹的形式在平台上进行宣传,从而引起投资人的关注。本文在基于搜索引擎优化方法的综合指标评价方法的基础上,提出了改进方案。在传统方法的基础上增加了聚类分析算法。该方法建立了完善的关键词优化策略管理机制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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