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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/32994

    Title: 以本體論為基礎的資料採礦方法應用於臺灣飲料商品產品及品牌光譜之研究
    Other Titles: The study of ontology-based approach to data mining techniques applied to product spectrum and brand spectrum of Taiwan beverage
    Authors: 楊逢杰;Yang, Feng-chich
    Contributors: 淡江大學管理科學研究所碩士班
    廖述賢;Liao, Shu-hsien
    Keywords: 本體論;資料採礦;市場區隔;產品光譜;品牌光譜;Ontology;data mining;Segmentation;product spectrum;brand spectrum
    Date: 2008
    Issue Date: 2010-01-11 03:06:36 (UTC+8)
    Abstract: 陳列在便利商店架上的各式飲料產品琳瑯滿目,綠茶、果汁、牛奶、咖啡、汽水、包裝水等,您會如何選擇呢?對於現代人來說,飲料早就是生活中不可或缺的一部份。目前飲料市場的商機日益擴大,飲料產品推陳出新的速度比起消費者所購買過的產品要快上許多,身為消費者的我們不難發現架上的飲料商品越來越雷同,光是選購就必須花上一些時間。因此我們不僅要問消費者忠誠於偏好的產品嗎?消費者對於口味挑剔嗎?那麼在消費者心中的產品有沒有偏好的排序?有沒有光譜般的漸層現象?


    In convenience stores, the sheer amount of various beverages on the shelves are stunning, from green tea, fruit juice, milk, coffee, soft drinks, packaged water and so on, how do you choose? For modern people, beverages have already become an indispensable part of life. As the beverage market expands, it’s not uncommon to come across similar beverages offered by different brands. We therefore spend much time choosing. Thus, we must ask: is the consumer loyal to a certain product or demanding in regards of taste? Does the consumer have a preference ranking of products? Is there a gradual spectrum phenomenon present?

    The thesis is based on the ontology concept, using four constructs—basic consumer data, data for consumer behavior, data for beverage product and data for promotion—to form a conceptive description and to design a questionnaire. We also used the ontology concept approach to form an association database that includes a basic consumer data database, a consumer behavior database, a beverage product database and a promotion database to describe consumer behavior.

    Finally, through the association rule and cluster analysis of data mining, we analyzed consumer adumbration, lifestyle habits and purchasing behavior. Then, we found each cluster’s consumer preference and product spectrum. The results of this research could provide suggestions and advice on management for future researchers, as well as help relevant practitioners increase their competitive capability.
    Appears in Collections:[Department of Management Sciences] Thesis

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