【摘要】：隨著互聯(lián)網(wǎng)技術(shù)的快速發(fā)展,各行業(yè)競(jìng)爭(zhēng)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(fèi)群體的購(gòu)物習(xí)慣、價(jià)格觀念是市場(chǎng)營(yíng)銷成功的關(guān)鍵,聰明的商家會(huì)根據(jù)不同的消費(fèi)者群體來(lái)制定有效的市場(chǎng)營(yíng)銷策略,包括優(yōu)化商品布局、設(shè)計(jì)促銷方案,使商場(chǎng)布局更加符合消費(fèi)者購(gòu)物習(xí)慣,從而提高商家業(yè)績(jī)和利潤(rùn),也為消費(fèi)者帶來(lái)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(diǎn)；其次,給出了關(guān)聯(lián)規(guī)則的相關(guān)理論,重點(diǎn)介紹了Aprior算法；再次,給出了聚類分析相關(guān)知識(shí)和主要算法,重點(diǎn)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(gè)月的顧客購(gòu)物記錄數(shù)據(jù)作為研究對(duì)象,利用SQL對(duì)數(shù)據(jù)進(jìn)行預(yù)處理,使用SPSS軟件對(duì)數(shù)據(jù)進(jìn)行關(guān)聯(lián)規(guī)則和聚類分析,通過(guò)聚類分析,本文把客戶分成四類,并對(duì)相應(yīng)結(jié)果進(jìn)行合理解釋。 數(shù)據(jù)挖掘是一個(gè)反復(fù)嘗試以便找出規(guī)則解釋現(xiàn)象的過(guò)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(duì)超市實(shí)施正確的營(yíng)銷方案起了很大的現(xiàn)實(shí)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(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：TP311.13

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