約略集為基礎的關聯法則於網路消費者推薦機制與改變行為之研究

淡江大學機構典藏 > 商管學院 > 管理科學學系暨研究所 > 學位論文 > Item 987654321/87513

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题名:	約略集為基礎的關聯法則於網路消費者推薦機制與改變行為之研究
其它题名:	The rough-set based association rule implements on online consumers for recommendation mechanism and changing behavior investigation
作者:	張筱可;Chang, Hsiao-Ko
贡献者:	淡江大學管理科學學系碩士班廖述賢;吳啟絹;Liao, Shu-Hsien;Wu, Chi-Chuan
关键词:	約略集理論;關聯法則;推薦機制;改變行為;資料採礦;Rough set theory;association rule;Recommendation Mechanism;Change Behavior;data mining
日期:	2012
上传时间:	2013-04-13 11:18:46 (UTC+8)
摘要:	現今21世紀的大環境中，因應電腦的普及化與社會經濟的復甦，對於網路購物已漸趨謂為風潮，在傳統的行銷系統中，幾乎每隔10-20年，就會有一套新的行銷系統出現，成為將產品銷售給終端消費者的新方法，所以在1990年代開始，網路與電子商務的盛行，至今因科技的進步、電腦的普及與消費者訴求購物的便利性，創造出所謂的「宅經濟」。因此，網路購物市場越來越蓬勃發展，而許許多多的消費者所傾向的是價格上低廉、交易機制的便利與安全性，因此，各網路購物平台的消費者忠誠度並不高，為獲得更廣大的消費者上網購買商品，與幫助企業的網站瀏覽量大增，提高各網路平台的消費者忠誠度，本研究將設計一個個人化的推薦機制，提供消費者更精緻的購物環境與服務。本研究結合了約略集與資料採礦中的關聯法則，著重於具有處理不確定性資料能力的規則產生，以助於行銷決策者可以準確的區隔市場，並發展以約略集為基礎之關聯演算法，加上層級分析法(AHP)之相對比重概念，建立內外部推薦機制，將適當的產品與平台通路推薦給消費者，端看是否能改變其消費行為。 Today in the 21st century environment, due to the popularity of computers and the social economic recovery, online shopping is getting that trend. In the traditional marketing system, almost every 10-20 years, will have new marketing system, to become a new method of selling product to the end of consumer. So, in the beginning of the 1990s, the prevalence of the Internet and e-commerce, so far, due to advances in technology, the popularity of computers and consumer demands of shopping convenience, and create the called”home economic”. Therefore, the online shopping market is increasingly prosperous development, while many consumers tend to price low, the convenience and security of the trading mechanism, therefore, the online shopping platform is not high consumer loyalty, in order to attract a wider consumer to purchase goods, and help enterprises significant increase in the website traffic and improve the network platform of consumer loyalty, this study will design a personalized recommendation mechanism, providing consumers with more refined shopping environment and service. In this study, a combination of rough sets and data mining of association rules, focus on the rules of dealing with uncertainty information generated to help the marketing decision-makers can accurately segment the market and the development of the rough-set based association rule algorithm, together with the relative weight of the concept of the Analytic Hierarchy Process (AHP), the establishment of external and referral mechanism will be the appropriate product and platform path recommended to consumers, the end to see if it can change their consumption behavior.
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