本文選題：質(zhì)量溯源 + 定向推薦系統(tǒng)�。� 參考：《中山大學》2012年碩士論文

【摘要】：由于近年來食品安全問題時常發(fā)生，實施食品質(zhì)量追溯已成為國際貿(mào)易發(fā)展的趨勢之一。農(nóng)產(chǎn)品質(zhì)量追溯系統(tǒng)即能為人民群眾提供優(yōu)質(zhì)安全的農(nóng)產(chǎn)品，又能提高企業(yè)優(yōu)質(zhì)農(nóng)產(chǎn)品在市場上的競爭力。 農(nóng)產(chǎn)品信息廣告推薦是農(nóng)產(chǎn)品質(zhì)量溯源的重要一環(huán)，因為它有助于提高人民群眾獲得優(yōu)質(zhì)農(nóng)產(chǎn)品信息的能力。本文的主要內(nèi)容便是關(guān)于農(nóng)產(chǎn)品質(zhì)量溯源系統(tǒng)中定向促銷廣告子系統(tǒng)的設(shè)計和實現(xiàn)，定向促銷廣告子系統(tǒng)的核心模塊是廣告交叉推薦模塊，廣告交叉推薦模塊采用BI-Polarslopeone算法和基于項目屬性相似性推薦算法實現(xiàn)廣告的個性化交叉推薦功能，，把最佳的并且消費者最可能感興趣的優(yōu)質(zhì)農(nóng)產(chǎn)品廣告推薦給消費者，從而讓使用本系統(tǒng)的消費者更容易獲取自己需要的產(chǎn)品信息。歸納起來，本文的主要研究內(nèi)容如下： （1）簡要論述農(nóng)產(chǎn)品質(zhì)量溯源系統(tǒng)中定向促銷廣告子系統(tǒng)的應用背景、意義及國內(nèi)外相關(guān)研究現(xiàn)狀。 （2）綜述協(xié)同過濾推薦技術(shù)、slopeone算法和基于項目屬性相似性推薦算法的基本原理，并對它們的特點進行分析，從而解釋了定向促銷廣告子系統(tǒng)中廣告交叉推薦模塊選取這兩種算法進行組合實現(xiàn)的原因。 （3）運用面向?qū)ο蠓治�、設(shè)計思想，設(shè)計并實現(xiàn)了定向促銷廣告子系統(tǒng)。具體來說，在系統(tǒng)需求分析中，借助系統(tǒng)功能結(jié)構(gòu)圖、UML用例圖和用例規(guī)約表對系統(tǒng)的功能需求進行分析；在系統(tǒng)設(shè)計中，運用系統(tǒng)架構(gòu)圖、UML包圖和網(wǎng)絡部署圖對系統(tǒng)的總體架構(gòu)設(shè)計進行闡述，運用UML時序圖、UML類圖對子系統(tǒng)的詳細設(shè)計進行闡述，運用流程圖和UML類圖對交叉推薦模塊中核心算法實現(xiàn)流程的設(shè)計進行闡述，其中交叉推薦模塊的算法實現(xiàn)程序在本文附錄中給出；在子系統(tǒng)實現(xiàn)中，除了闡述系統(tǒng)的開發(fā)與運行環(huán)境外，還運用模擬用戶數(shù)據(jù)集對系統(tǒng)交叉推薦模塊的運行情況進行闡述，并對運行效果進行評價。
[Abstract]:Due to the frequent occurrence of food safety problems in recent years, the implementation of food quality traceability has become one of the trends in the development of international trade.The quality traceability system of agricultural products can not only provide the people with high quality and safety agricultural products, but also improve the competitiveness of enterprises' high quality agricultural products in the market.The recommendation of agricultural product information advertisement is an important link in tracing the quality of agricultural products, because it is helpful to improve the people's ability to obtain high quality agricultural product information.The main content of this paper is about the design and implementation of targeted promotion advertising subsystem in the traceability system of agricultural products quality. The core module of targeted promotion advertising subsystem is advertising cross-recommendation module.The advertising cross recommendation module uses BI-Polarslopeone algorithm and item attribute similarity recommendation algorithm to realize the personalized cross recommendation function of advertising, and recommends the best and most likely consumers interested in high quality agricultural products advertising to consumers.Thus, it is easier for consumers using this system to obtain the product information they need.In summary, the main contents of this paper are as follows:This paper briefly discusses the application background, significance and research status of orientation promotion advertising subsystem in the traceability system of agricultural products quality.This paper summarizes the basic principles of collaborative filtering recommendation technology, slopeone algorithm and item attribute similarity recommendation algorithm, and analyzes their characteristics.The reason why the two algorithms are combined is explained.Using object-oriented analysis and design idea, we design and implement the advertising subsystem of targeted promotion.Specifically, in the system requirement analysis, the UML use case diagram and the use case specification table are used to analyze the functional requirements of the system; in the system design, the function requirements of the system are analyzed with the help of the UML use case diagram and the use case specification table.The overall architecture design of the system is described by using the system architecture diagram and the network deployment diagram, and the detailed design of the subsystem is described by using the UML sequence diagram and the UML class diagram.The flow chart and UML class diagram are used to explain the design of the core algorithm realization flow in the cross recommendation module, in which the algorithm realization program of the cross recommendation module is given in the appendix of this paper, and in the implementation of the subsystem, the algorithm realization procedure of the cross recommendation module is given in this paper.Besides the development and running environment of the system, the running situation of the cross recommendation module of the system is described by using the simulated user data set, and the operation effect is evaluated.
【學位授予單位】：中山大學
【學位級別】：碩士
【學位授予年份】：2012
【分類號】：TP311.52

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