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Research on Categorization of Animation Effect Based on Data Mining

机译:基于数据挖掘的动画效果分类研究

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Nowadays, the production process of animation effect is increasingly developed, and its effect is also growing better. But in most cases, the categorization of special effect added to the animation is confusing due to excessive variations. Data mining will desirably solve the problem of animation effect categorization, so the application of data mining in the animation effect categorization becomes the hot spot in research and analysis at present. This article makes a detailed analysis on relevant algorithm of data mining technology, that is, the k application of averaging method, k central point method and relational degree algorithm in problem of animation effect categorization. It provides a clear method of categorization for animation effect. Thereafter, it also concludes the accuracy of animation effect categorization can be greatly improved through reasonable algorithm integration in the treatment of animation effect categorization by data mining.Key words: data mining / animation effect categorization / cluster analysis / relational degree
机译:如今,动画效果的制作过程日益发展,效果也越来越好。但是在大多数情况下,由于过多的变化,添加到动画中的特殊效果的分类令人困惑。数据挖掘有望解决动画效果分类问题,因此数据挖掘在动画效果分类中的应用成为当前研究和分析的热点。详细分析了数据挖掘技术的相关算法,即平均法,k中心点法和关联度算法在动画效果分类问题中的k个应用。它提供了一种清晰的动画效果分类方法。进而得出结论,通过合理的算法集成,在数据挖掘对动画效果分类的处理中,可以大大提高动画效果分类的准确性。关键词:数据挖掘/动画效果分类/聚类分析/关系度

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