Analysis Online Shopping Behavior of Consumer Using Decision Tree

Lei Yue Yao; Jian Ying Xiong

doi:10.4028/www.scientific.net/AMR.271-273.891

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 271-273Analysis Online Shopping Behavior of Consumer...

Analysis Online Shopping Behavior of Consumer Using Decision Tree

Abstract:

Trading failure is the main reason for a dispute of C2C e-commerce. So predict the behavior of transactions can assist buyers and sellers negotiated transactions, helps to reduce transaction disputes. Separate the success and failure purchase record, then establish decision-making model through the C5.0 decision tree and RFM(Recency, Frequency, Monetary) model on consumer purchase behavior data, quantify the importance of the decision variables, the demonstration experiment shows the prediction accuracy is more than 80%.

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Periodical:

Advanced Materials Research (Volumes 271-273)

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891-894

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.271-273.891

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Online since:

July 2011

Authors:

Lei Yue Yao, Jian Ying Xiong

Keywords:

C 5.0, Decision Tree, Trading Predict

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