【摘要】：隨著互聯(lián)網(wǎng)技術(shù)的高速發(fā)展,電子商務(wù)產(chǎn)業(yè)正逐步占領(lǐng)著傳統(tǒng)產(chǎn)業(yè)的市場(chǎng)份額,越來(lái)越多的傳統(tǒng)行業(yè)開始轉(zhuǎn)變或發(fā)展電商業(yè)務(wù),2014年,也是電子商務(wù)發(fā)展最為關(guān)鍵的一年,阿里巴巴赴美上市不僅成就了馬云中國(guó)首富的地位,更讓全世界看到了這個(gè)全球最大的移動(dòng)電商公司是來(lái)自中國(guó)。馬云曾宣稱21世紀(jì)阿里要作一個(gè)偉大的數(shù)據(jù)公司,這讓大家想到阿里巴巴的大數(shù)據(jù)有多么可怕。如何將這些數(shù)據(jù)轉(zhuǎn)換成有用的信息,為公司創(chuàng)造更多的潛在利潤(rùn),數(shù)據(jù)挖掘技術(shù)在其中起止舉足輕重的作用,它可以有效地幫助企業(yè)分析網(wǎng)絡(luò)中的大量數(shù)據(jù),發(fā)現(xiàn)其隱藏的規(guī)律性,篩選出有效信息,進(jìn)而指導(dǎo)企業(yè)調(diào)整營(yíng)銷策略,給客戶提供更加個(gè)性化的高效率服務(wù)[1]。本文首先對(duì)國(guó)內(nèi)外電子商務(wù)現(xiàn)狀進(jìn)行分析,了解和學(xué)習(xí)目前流行的電子商務(wù)網(wǎng)站框架,分析其功能和結(jié)構(gòu)設(shè)計(jì),并就如何能夠增加用戶體驗(yàn)度做了進(jìn)一步的研究,完成本系統(tǒng)的總體設(shè)計(jì),包括整個(gè)電子圖書商城系統(tǒng)的圖書、訂單、顧客信息管理,用戶登錄注冊(cè)、查詢書目、購(gòu)物車管理、圖書評(píng)論等功能。然后著重研究各大電子商務(wù)網(wǎng)站中的個(gè)性化推薦功能,從分析和研究國(guó)內(nèi)外流行電子商務(wù)網(wǎng)站,從而實(shí)現(xiàn)本系統(tǒng)的個(gè)性化推薦功能[2]。本系統(tǒng)的個(gè)性化推薦功能圍繞數(shù)據(jù)挖掘的兩個(gè)分析模型開始,一個(gè)是對(duì)客戶數(shù)據(jù)預(yù)處理模型,另一個(gè)是基于遺傳算法的關(guān)聯(lián)規(guī)則算法模型。數(shù)據(jù)挖掘技術(shù)在電子商務(wù)中的應(yīng)用可以將電子圖書商城的瀏覽者轉(zhuǎn)變?yōu)橘?gòu)買者。通過(guò)系統(tǒng)中的個(gè)性化推薦功能,分析瀏覽者的上網(wǎng)軌跡、興趣愛好,從而向其推薦適合自己的商品,為商家提供利潤(rùn)。當(dāng)用戶要結(jié)賬時(shí),可以根據(jù)已經(jīng)購(gòu)買的商品,推薦同一類型的打折商品或熱門商品,加強(qiáng)原有的產(chǎn)品或服務(wù),從而提高商品之間的關(guān)聯(lián)能力。個(gè)性化的服務(wù)使網(wǎng)站與客戶之間建立起了一條牢固的紐帶,使網(wǎng)站成為客戶在日常生活中必不可少的一部分,通過(guò)使用個(gè)性化推薦功能,可以輕松的得到客戶想要的商品,將顧客更多地吸引到自己的網(wǎng)站[3],從而提高客戶對(duì)電子商務(wù)網(wǎng)站的忠誠(chéng)度。
[Abstract]:With the rapid development of Internet technology, e-commerce industry is gradually occupying the market share of traditional industries. More and more traditional industries begin to change or develop e-commerce business. 2014 is also the most critical year for the development of e-commerce. Alibaba's listing in the United States not only made Ma the richest man in China, but also showed the world that the world's largest mobile e-commerce company is from China. Ma's claim that Ali will be a great data company in the 21st century reminds us of Alibaba's big data. How to convert these data into useful information and create more potential profits for companies, data mining technology plays an important role in it, it can effectively help enterprises to analyze a large amount of data in the network. Find its hidden regularity, screen out the effective information, then guide the enterprise to adjust the marketing strategy, and provide more personalized and high efficiency service to the customer [1]. In this paper, we first analyze the current situation of e-commerce at home and abroad, understand and study the current popular e-commerce website framework, analyze its function and structure design, and do further research on how to increase the degree of user experience. Complete the overall design of the system, including the entire e-book mall system of books, orders, customer information management, user login registration, query bibliography, shopping cart management, book review and other functions. Then, the individualized recommendation function of each E-commerce website is studied emphatically, and the individualized recommendation function of this system is realized by analyzing and studying the popular E-commerce websites at home and abroad. The personalized recommendation function of this system begins with two analysis models of data mining, one is the pre-processing model of customer data, the other is the association rule algorithm model based on genetic algorithm. The application of data mining technology in e-commerce can change the visitors of e-book mall into buyers. Through the personalized recommendation function in the system, the article analyzes the online track and interests of the visitors, so as to recommend their own products and provide profit for the merchants. When users want to check out, they can recommend the same type of discounted goods or hot goods according to the goods they have purchased, so as to strengthen the original products or services, so as to improve the ability of connection between goods. The personalized service has established a strong bond between the website and the customer, making the website become an indispensable part of the customer's daily life. Through the use of personalized recommendation function, you can easily get the goods that the customer wants. Attract more customers to their own websites [3], thus increasing customer loyalty to e-commerce sites.
【學(xué)位授予單位】：北京工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TP311.13;TP393.092
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本文編號(hào)：2281522