利用分類分析發掘消費者最適性之產品項目

Using Classification Analysis to Find Consumers' Most Adaptive Product Items

陳垂呈(Chui-Cheng Chen)

《輔仁管理評論》 15卷1期 (2008/01) Pp. 17-43

https://doi.org/10.29698/FJMR.200801.0002

摘要

在本論文中，我們以消費者之交易資料爲探勘的資料來源，每一筆交易資料除了記錄有消費者曾經購買過的產品項目，也記錄著其購買的次序性，以某一消費者爲探勘的目標，利用分類分析(classification analysis)分別從以下兩方面發掘此消費者最適性的產品項目：一是只考量產品項目是否出現在交易資料中，文中設計一個建構決策樹的方法，以顯示那些產品項目與此消費者之間有關聯性的傾向特徵，藉此做爲發掘此消費者最適性之產品項目的依據；二是考量產品項目具有購買次序性，文中設計一個建構決策樹的方法，以顯示那些產品項目與此消費者之間具有購買次序的關聯性傾向特徵，藉此做爲發掘具有購買次序之此消費者最適性的產品項目的依據。我們根據所提出的方法，設計與建置一個發掘消費者最適性之產品項目的探勘系統。

關鍵字

交易資料 ； 分類分析 ； 次序性

並列摘要

In this paper, we use consumers' transaction data as the source data of mining. Each transaction data contains a consumer ever bought product items with sequence. We let one consumer as the target of mining and use classification analysis to find the consumer's most adaptive product items from two aspects. One is to consider whether product items are contained in transaction data. A method is presented to construct a decision tree that shows whichever product items to have association with the consumer. The consumer's most adaptive produce items are found from the decision tree. The other is to consider extra the sequences of buying product items. A method is presented to construct a decision tree that shows whichever product items to have sequential association with the consumer. The consumer's most adaptive produce items with sequence are found from the decision tree. We design and construct a mining system to find consumers' most adaptive product items according to the above methods.

並列關鍵字

transaction data ； classification analysis ； sequence

參考文獻

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