FCD-KNN Clustering Evaluation Method for Cigarette Value Perception Based on Customer Behavior Data
There are many features of cigarettes.If all features are included in the evaluation scope,it will not only increase the complexity and workload of the evaluation,but also affect the separability and accuracy of the evaluation results due to information redundancy.Therefore,a FCD-KNN clustering evaluation method for cig-arette value perception based on customer behavior data was studied.Firstly,after standardizing customer be-havior data and quantifing some non numerical data,FCD(Frequent Combining Digiting)method was used to mine customer behavior data and extract multiple features related to cigarette value perception.Then,under KNN(K Nearest Neighbor)clustering algorithm,a cigarette value perception evaluation system was construc-ted by calculating feature similarity and selecting features with strong correlation with value perception and ac-curate reflection of product value based on high similarity.The experimental results show that the Davies-Bouldin index of this method was relatively small,while the Calinski-Harabasz index was relatively high,en-suring the separability and accuracy of the evaluation results.
Customer behavior dataFCD-KNN clustering algorithmCigarette value perceptionSimi-larity features