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Application and Research on Data Mining in E-Commerce Recommendation System

Author: HeYun
Tutor: MoDongYan
School: Dalian Jiaotong University
Course: Business management
Keywords: E-commerce Data Mining Association rules Recommended system
CLC: TP311.13
Type: Master's thesis
Year: 2010
Downloads: 524
Quote: 3
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Abstract


With the popularity of the Internet , e-commerce has become an increasingly important commodity sales model , the selection of products to provide users with more and more e-commerce system enables users to stay at home . But at the same time more and more types of goods and the structure of the site has also become more complex , users often get lost in a large number of goods space , unable to find the goods they need . In the increasingly fierce competitive environment , a good product recommendation system for the user to provide needed goods recommended in order to effectively retain customers , to prevent the loss of customers and increase the sales force and competitiveness . Commodity recommendation system has good prospects for the development and application of e-commerce systems , and has gradually become an important research content of the e-commerce application technology . With the continuous expansion of the scale of e-commerce , commodity recommendation system is also facing a series of challenges , such as the recommended efficiency , recommended accuracy . The major challenges faced by the commodity recommendation system , from the following aspects of e - commerce recommendation system as well as the techniques used , the analysis and research . First, a detailed analysis of the technical characteristics of the various data mining and Web mining and its important role in e-commerce . Followed by the introduction of e-commerce recommendation system and its workflow . At the same time gives a simple model of e-commerce recommendation system , from data preprocessing , pattern discovery , pattern analysis and model applications at all stages of the workflow and key technologies of e-commerce recommendation system . Finally, to improve their specific application characteristics of Apriori algorithm so that it can be efficiently applied recommendation system , give full play to its role in e-commerce recommendation system . In this paper, the improved Apriori algorithm , there are still many shortcomings to be further improved , in particular, the accuracy and efficiency problems . Which improve the efficiency of the algorithm is an important issue of research in various algorithms association rules . With the deepening of algorithm analysis and research , we believe that user-oriented e-commerce personalized recommendation services will be more efficient .

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer software > Program design,software engineering > Programming > Database theory and systems
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