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Association Rules Mining for Identifying Popular Ingredients on YouTube Cooking Recipes Videos

机译:关联规则挖掘,以识别YouTube烹饪食谱视频中的流行成分

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YouTube provides a lot of videos that will be able to create dataset. YouTube video has some characteristics on number of views, likes, dislikes and comments. Association rules mining able to find the most dominant item in a dataset. This research investigates 40 random videos on YouTube by implementing association rules mining algorithm to find what is the most ingredients used in Indonesia cooking recipes. This research found that the most liked video use 2 main ingredient which are garlic and onion. This research also implements IST-EFP algorithm for reducing the dimensional of the dataset without loss on important rules obtained. This research found IST-EFP able to reduce 19% on dataset dimension with 0.7% loss on rules obtained.
机译:YouTube提供了许多可以创建数据集的视频。 YouTube视频在观看次数,喜欢,不喜欢和评论方面有一些特点。关联规则挖掘能够在数据集中找到最主要的项目。这项研究通过实施关联规则挖掘算法,调查了YouTube上的40个随机视频,以找出印尼烹饪食谱中使用最多的成分。这项研究发现,最喜欢的视频使用2种主要成分,即大蒜和洋葱。该研究还实现了IST-EFP算法,以减少数据集的维数,而不会丢失所获得的重要规则。这项研究发现,IST-EFP可以将数据集维度减少19%,而获得的规则损失0.7%。

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