本文選題：電子商務 + 關聯(lián)規(guī)則挖掘��； 參考：《五邑大學》2013年碩士論文

【摘要】：隨著Internet技術的不斷發(fā)展,電子商務這一現(xiàn)代商業(yè)模式以其高效率、低成本和不受時空限制的特點成為企業(yè)商務活動發(fā)展的趨勢。而天貓商城是亞洲最大的電子商務交易平臺,其擁有近5億的注冊用戶數(shù),每天有超過6000萬的固定訪客,同時每天的在線商品數(shù)已經(jīng)超過了8億件,是中國電子商務網(wǎng)站發(fā)展的奇跡。巨大數(shù)量的用戶創(chuàng)造了巨大的交易數(shù)據(jù),然而從這些繁雜的交易數(shù)據(jù)中我們能得到有價值的信息卻相對較少,如何能從這些交易數(shù)據(jù)中獲取有利于賣家商業(yè)運作以及制定營銷策略的信息成為不容忽略的重要問題。 關聯(lián)規(guī)則挖掘(Association Rules Mining)是通過分析每個數(shù)據(jù),從大量數(shù)據(jù)中尋找規(guī)律的技術。該技術的出現(xiàn)為電子商務行為提供了強大的數(shù)據(jù)分析支持,將關聯(lián)規(guī)則挖掘技術應用到大量的、復雜的交易數(shù)據(jù)中去,才能體現(xiàn)出關聯(lián)規(guī)則挖掘技術的研究價值,毫無疑問電子商務是數(shù)據(jù)挖掘應用的最佳對象。通過對交易數(shù)據(jù)的挖掘,如商品的交易數(shù)量,交易種類,交易時間等,提取相關的交易知識,將復雜,無序的交易數(shù)據(jù),變成賣家分析市場,制定經(jīng)營策略,管理客戶關系的有力依據(jù),從而實現(xiàn)電子商務活動的真正價值。 論文討論了關聯(lián)規(guī)則挖掘中的主要算法之一,Apriori算法,分析了該算法在挖掘大量交易數(shù)據(jù)中的具體實現(xiàn)過程。通過記錄大量的天貓商城交易數(shù)據(jù),建立交易數(shù)據(jù)事務數(shù)據(jù)庫,分別從買家和商品兩個角度進行討論,對實際數(shù)據(jù)進行算法應用分析,結合實例證明了該算法在電子商務數(shù)據(jù)應用關聯(lián)規(guī)則挖掘中的有效性,并根據(jù)算法挖掘得到的關聯(lián)規(guī)則,結合微博營銷的方式,最終達到提升銷售的效果。
[Abstract]:With the development of Internet technology, E-commerce, as a modern business model, has become the trend of the development of business activities because of its high efficiency, low cost and no limitation of time and space. Tmall Mall is the largest e-commerce trading platform in Asia, with nearly 500 million registered users, more than 60 million regular visitors a day, and more than 800 million online goods every day. It is the miracle of the development of Chinese e-commerce website. A huge number of users create huge amounts of transaction data, but we get relatively little valuable information from these complex trading data. How to obtain the information that is beneficial to the seller's business operation and make the marketing strategy from these transaction data has become an important problem that can not be ignored. Association Rules Mining is a technique to find rules from a large number of data by analyzing each data. The emergence of this technology provides a powerful data analysis support for e-business behavior. Only when association rules mining technology is applied to a large number of complex transaction data, can the research value of association rule mining technology be reflected. There is no doubt that electronic commerce is the best object for data mining applications. Through the mining of transaction data, such as the quantity, type and time of trade, and so on, the relevant transaction knowledge is extracted, and the complicated and disordered transaction data is turned into the seller to analyze the market and formulate the management strategy. Management of customer relationships on the basis of strength, so as to achieve the real value of e-commerce activities. In this paper, the Apriori algorithm, one of the main algorithms in association rule mining, is discussed, and the implementation process of the algorithm in mining a large number of transaction data is analyzed. By recording a large number of trading data of Tmall Mall, establishing transaction data transaction database, discussing the transaction data from two angles of buyer and commodity, analyzing the algorithm application of the actual data. The validity of the algorithm in the application of association rules in electronic commerce data is proved by an example. According to the association rules obtained by the algorithm and the marketing method of Weibo, the effect of sales promotion is finally achieved.
【學位授予單位】：五邑大學
【學位級別】：碩士
【學位授予年份】：2013
【分類號】：TP311.13;F724.6

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