本文選題：電子商務(wù) + 個(gè)性化推薦��； 參考：《東北大學(xué)》2014年碩士論文

【摘要】：電子商務(wù)的發(fā)展為客戶提供了更多的可選商品,同時(shí)也帶來(lái)了“信息超載”問(wèn)題�？蛻粼诿鎸�(duì)海量商品時(shí)往往顯得很迷茫。為此,電子商務(wù)個(gè)性化推薦應(yīng)運(yùn)而生。它利用電子商務(wù)網(wǎng)站平臺(tái),模擬商店的銷售人員向客戶推薦商品,克服了信息過(guò)載的問(wèn)題。對(duì)于客戶來(lái)說(shuō),電子商務(wù)個(gè)性化推薦能幫助其從海量商品信息中發(fā)現(xiàn)自己感興趣的商品；對(duì)于商家來(lái)說(shuō),電子商務(wù)個(gè)性化推薦能幫助其實(shí)現(xiàn)差異性經(jīng)營(yíng),同時(shí)提高網(wǎng)站的交叉銷售,為其帶來(lái)巨大的經(jīng)濟(jì)利益。目前,關(guān)于電子商務(wù)個(gè)性化推薦問(wèn)題的研究已經(jīng)引起了企業(yè)界及學(xué)者界的廣泛關(guān)注,并取得了一些研究成果。然而,已有的研究成果很少關(guān)注客戶的分類,以及不同類型客戶的偏好分析。此外,商品質(zhì)量水平和商家在銷售過(guò)程中提供的服務(wù)水平是影響客戶做出是否進(jìn)行購(gòu)買決策的兩個(gè)重要因素。因此,需要對(duì)電子商務(wù)個(gè)性化推薦問(wèn)題進(jìn)行進(jìn)一步研究,即按照客戶是否給出需求將客戶進(jìn)行分類,并分別給出有針對(duì)性的推薦方法,同時(shí)在推薦中綜合考慮質(zhì)量和服務(wù)水平,是一個(gè)值得關(guān)注的研究課題,具有重要的理論意義和現(xiàn)實(shí)意義。已有研究成果表明,基于相似案例的分析方法符合客戶的思維特點(diǎn),推薦結(jié)果容易被客戶所接受,因此,將基于相似案例分析的方法引入到電子商務(wù)個(gè)性化推薦中,并同時(shí)考慮客戶的分類以及商品的質(zhì)量水平和商家的服務(wù)水平的研究是有必要的。本文對(duì)基于相似案例分析的電子商務(wù)個(gè)性化推薦方法進(jìn)行了深入研究,主要開(kāi)展了以下幾個(gè)方面的研究工作：(1)給出了基于相似案例分析的電子商務(wù)個(gè)性化推薦問(wèn)題的描述及研究框架。為了有針對(duì)性地分析客戶信息,將電子商務(wù)個(gè)性化推薦問(wèn)題按照客戶在登錄網(wǎng)站時(shí)是否具有需求分為兩類：考慮客戶潛在需求的電子商務(wù)個(gè)性化推薦問(wèn)題和考慮客戶給出需求的電子商務(wù)個(gè)性化推薦問(wèn)題。此外,分別給出了基于相似案例分析的電子商務(wù)個(gè)性化推薦問(wèn)題的一般性描述以及研究框架。這些基礎(chǔ)性的研究工作為電子商務(wù)個(gè)性化推薦的研究提供了理論指導(dǎo)框架和分析框架,并為研究電子商務(wù)個(gè)性化推薦的擴(kuò)展與應(yīng)用提供了堅(jiān)實(shí)的基礎(chǔ)。(2)研究了考慮客戶潛在需求的電子商務(wù)個(gè)性化推薦方法。具體地,針對(duì)具有潛在需求的客戶,提出了一種基于相似案例分析的考慮客戶潛在需求的推薦方法。首先,綜合考慮客戶的注冊(cè)信息、行為信息和評(píng)價(jià)信息對(duì)該類型的客戶的偏好分析,給出考慮客戶潛在需求的案例表示與問(wèn)題描述；然后,根據(jù)客戶注冊(cè)信息計(jì)算案例間的相似度,構(gòu)建了相似客戶注冊(cè)信息案例集；再根據(jù)客戶是否有購(gòu)買行為分別計(jì)算關(guān)于客戶行為的案例相似度,并構(gòu)建了初始商品集；最后,針對(duì)初始商品集,綜合考慮質(zhì)量和服務(wù)水平,從而確定出推薦商品集。(3)研究了考慮客戶給出需求的電子商務(wù)個(gè)性化推薦方法。具體地,針對(duì)給出需求的客戶,提出了一種基于相似案例分析的考慮客戶給出需求的推薦方法。首先,綜合考慮客戶的需求信息、行為信息和評(píng)價(jià)信息對(duì)該類型的客戶的偏好分析,給出了考慮客戶給出需求的案例表示與問(wèn)題描述；然后,根據(jù)客戶需求信息計(jì)算客戶需求與商品集中商品的相似度,構(gòu)建了需求商品集；再根據(jù)客戶是否有購(gòu)買行為分別計(jì)算目標(biāo)案例與購(gòu)買過(guò)需求商品集中商品的案例關(guān)于客戶行為的相似度,并構(gòu)建了初始商品集；最后,針對(duì)初始商品集,綜合考慮質(zhì)量和服務(wù)水平,從而確定出推薦的商品集。本文提出的基于相似案例分析的電子商務(wù)個(gè)性化推薦方法,考慮了客戶類型、質(zhì)量和服務(wù)水平對(duì)個(gè)性化推薦的影響,為解決電子商務(wù)個(gè)性化推薦問(wèn)題提供了可參考的方法。
[Abstract]:The development of e-commerce provides more optional items for customers, and it also brings "information overload". Customers tend to be confused when facing large quantities of goods. For this reason, personalized recommendation of E-commerce arises at the historic moment. It uses e-commerce website platform to simulate store salespeople to recommend goods to customers and overcome the letter. For customers, personalized recommendation of e-commerce can help them find the goods they are interested in from mass commodity information. For businesses, personalized recommendation of e-commerce can help to realize the difference operation, at the same time, improve the cross selling of the website, and bring huge economic benefits to them. The research on personalized recommendation of sub business has attracted wide attention from the business community and the scholars, and has obtained some research results. However, the existing research results seldom pay attention to the classification of customers and the preference analysis of different types of customers. In addition, the quality level of goods and the service level provided by the merchants in the process of sales are the shadow. The customer makes two important factors to decide whether to make a purchase decision. Therefore, it is necessary to further study the personalized recommendation problem of e-commerce, that is, to classify the customers according to the needs of the customers, and to give the targeted methods of recommendation respectively. At the same time, it is worth to consider the quality and service level in the recommendation. The research topic of concern is of great theoretical and practical significance. The existing research results show that the analytical methods based on similar cases conform to the customer's thinking characteristics and the recommended results are easily accepted by the customers. Therefore, the method based on similar case analysis is introduced into the personalized recommendation of the electric sub business, and the customer's score is considered at the same time. It is necessary to study the quality level of the class and the commodity and the service level of the business. This paper makes an in-depth study on the personalized recommendation method of e-commerce based on similar case analysis. The main research work is carried out in the following aspects: (1) the description of personalized recommendation of e-commerce based on similar case analysis is given. In order to analyze the customer information, the problem of e-commerce personalized recommendation is divided into two categories according to the requirements of the customer on the web site: the personalized recommendation of electronic commerce considering the customer's potential demand and the personalized recommendation of the electric sub commerce considering the customer's requirement. The general description and research framework of e-commerce personalized recommendation based on similar case analysis are presented. These basic research provides a theoretical framework and an analytical framework for the research on personalized recommendation of e-commerce, and provides a solid foundation for the study of the extension and application of personalized recommendation in e-commerce. (2) This paper studies the personalized recommendation method of e-commerce in consideration of the potential needs of customers. Specifically, a recommendation method based on similar case analysis is proposed for customers with potential needs. Firstly, the preference of customer's registration information, behavior information and evaluation information is considered. The case representation and problem description that consider the customer's potential demand is given. Then, according to the similarity of the customer registration information, a case set of similar customer registration information is constructed, and the case similarity of customer behavior is calculated according to whether the customer has the purchase behavior, and the initial commodity set is constructed. Finally, the target is set up. Initial commodity set, comprehensive consideration of quality and service level, so as to determine the recommended commodity set. (3) study the personalized recommendation method of e-commerce in consideration of customer requirements. Specifically, a recommendation method based on similar case analysis is proposed for customers to give needs based on similar case analysis. First, consider the customers comprehensively. The demand information, behavior information and evaluation information on this type of customer's preference analysis, give the case representation and problem description considering the customer's requirement, then, calculate the similarity between the customer's demand and the commodity centralized commodity according to the customer's demand information, and build the demand quotient set; and then according to whether the customer has the purchase behavior or not, We calculate the similarity between the target case and the case about the purchase of the commodity in the demand commodity, and build the initial commodity set. Finally, considering the quality and service level of the initial commodity set, the recommended commodity set is determined. The personalized recommendation method based on the phase like analysis in this paper is based on the phase like case analysis. Considering the influence of customer type, quality and service level on personalized recommendation, it provides a reference method for solving personalized recommendation problem in e-commerce.
【學(xué)位授予單位】：東北大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：F724.6

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