【摘要】：隨著互聯(lián)網(wǎng)技術(shù)的快速發(fā)展,各行業(yè)競爭也日趨激烈,客戶已成為關(guān)系企業(yè)成敗的最重要資源,理解不同消費群體的購物習(xí)慣、價格觀念是市場營銷成功的關(guān)鍵,聰明的商家會根據(jù)不同的消費者群體來制定有效的市場營銷策略,包括優(yōu)化商品布局、設(shè)計促銷方案,使商場布局更加符合消費者購物習(xí)慣,從而提高商家業(yè)績和利潤,也為消費者帶來更多的方便。 本文以零售業(yè)為例,探討了關(guān)聯(lián)規(guī)則和聚類分析在數(shù)據(jù)挖掘中的應(yīng)用。首先,介紹了數(shù)據(jù)挖掘概況及其特點；其次,給出了關(guān)聯(lián)規(guī)則的相關(guān)理論,重點介紹了Aprior算法；再次,給出了聚類分析相關(guān)知識和主要算法,重點介紹了系統(tǒng)聚類法和快速聚類法；最后,為了更好地理解關(guān)聯(lián)和聚類分析在數(shù)據(jù)挖掘中應(yīng)用,本文選取了某商業(yè)區(qū)10家之佳便利店一個月的顧客購物記錄數(shù)據(jù)作為研究對象,利用SQL對數(shù)據(jù)進(jìn)行預(yù)處理,使用SPSS軟件對數(shù)據(jù)進(jìn)行關(guān)聯(lián)規(guī)則和聚類分析,通過聚類分析,本文把客戶分成四類,并對相應(yīng)結(jié)果進(jìn)行合理解釋。 數(shù)據(jù)挖掘是一個反復(fù)嘗試以便找出規(guī)則解釋現(xiàn)象的過程,它需要熟練掌握挖掘算法和了解具體的行業(yè)背景。本文挖掘的規(guī)則對超市實施正確的營銷方案起了很大的現(xiàn)實指導(dǎo)意義。
[Abstract]:With the rapid development of Internet technology, the competition in various industries is becoming more and more fierce. Customers have become the most important resource related to the success or failure of enterprises. To understand the shopping habits of different consumer groups, the price concept is the key to the success of marketing. Smart businesses make effective marketing strategies based on different consumer groups, including optimizing product layout, designing promotional programs, making store layout more in line with consumer shopping habits, and thus improving business performance and profits. It also brings more convenience to consumers. This paper discusses the application of association rules and clustering analysis in data mining. Firstly, the general situation and characteristics of data mining are introduced. Secondly, the related theory of association rules is given, and the Aprior algorithm is emphasized. Thirdly, the related knowledge and main algorithms of clustering analysis are given. Finally, in order to better understand the application of association and cluster analysis in data mining, the system clustering method and fast clustering method are introduced. In this paper, the customer shopping record data of 10 best convenience stores in a commercial district are selected as the research object. The data are preprocessed by SQL, association rules and clustering analysis are carried out by SPSS software, and the data are analyzed by clustering analysis. This article divides the customer into four categories, and carries on the reasonable explanation to the corresponding result. Data mining is a process of repeatedly trying to find out the phenomenon of rule interpretation. It requires mastering the mining algorithm and understanding the specific background of the industry. This article excavates the rule to the supermarket to carry out the correct marketing plan to play the very big realistic guiding significance.
【學(xué)位授予單位】：云南大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：TP311.13

【參考文獻(xiàn)】

相關(guān)期刊論文 前6條

1 孟大為;數(shù)據(jù)挖掘及其在電廠中的應(yīng)用[J];發(fā)電設(shè)備;2004年S1期

2 王熙照;趙東壘;;基于規(guī)則興趣度的關(guān)聯(lián)分類[J];計算機(jī)工程與應(yīng)用;2007年25期

3 朱祥玉;侯德文;陳希;;對關(guān)聯(lián)規(guī)則挖掘Apriori算法的進(jìn)一步改進(jìn)[J];信息技術(shù)與信息化;2005年06期

4 盧云燕;;數(shù)據(jù)挖掘技術(shù)[J];重慶教育學(xué)院學(xué)報;2006年03期

5 皮德常,秦小麟,王寧生;基于動態(tài)剪枝的關(guān)聯(lián)規(guī)則挖掘算法[J];小型微型計算機(jī)系統(tǒng);2004年10期

6 徐守軍,高波,甄蓓,彭奕,王東根,王玉民,吳樂山;數(shù)據(jù)挖掘技術(shù)在科研管理中應(yīng)用前景初探[J];中華醫(yī)學(xué)科研管理雜志;2005年04期

，

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