Application of Decision Tree-Based Classification Algorithm on Content Marketing

Yi Liu, Shuo Yang and Miaochao Chen

Journal of Mathematics, 2022, vol. 2022, 1-10

Abstract: Traditional content marketing methods resort grossly to market requirements but barely obtain relatively accurate marketing prediction under loads of requirements. Machine learning-based approaches nowadays are widely used in multiple fields as they involve a training process to deal with big data problems. In this paper, decision tree-based methods are introduced to the field of content marketing, and decision tree-based methods intrinsically follow the process of human decision making. Specifically, this paper considers a well-known method, called C4.5, which can deal well with continuous values. Based on four validation metrics, experimental results obtained from several machine learning-based methods indicate that the C4.5-based decision tree method has the ability to handle the content marketing dataset. The results show that the decision tree-based method can provide reasonable and accurate suggestions for content marketing.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jjmath:6469054

DOI: 10.1155/2022/6469054

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