【摘要】： 在建設(shè)數(shù)字化終身學(xué)習(xí)體系的大背景下,E-Learning個性化推薦系統(tǒng)作為終身學(xué)習(xí)體系中最重要的學(xué)習(xí)方式,受到廣泛的關(guān)注。個性化推薦系統(tǒng)(簡稱PRS)最早應(yīng)用于電子商務(wù)和信息服務(wù)領(lǐng)域,現(xiàn)已相對成熟。而PRS在E-Learning中的應(yīng)用尚處于摸索階段。鑒于此,筆者以電子商務(wù)領(lǐng)域的個性化推薦系統(tǒng)為切入點,選取其中成功的推薦系統(tǒng)案例做研究,獲取個性化推薦系統(tǒng)應(yīng)用的成功經(jīng)驗,并從中提取出對E-Learning系統(tǒng)個性化建設(shè)的啟示,最終探討出E-Learning個性化系統(tǒng)的推薦策略。 本研究以個性化推薦理論作為基本的理論基礎(chǔ)。首先采用文獻(xiàn)研究法,探討出個性化推薦理論的內(nèi)涵,并對當(dāng)前個性化推薦的關(guān)鍵技術(shù)進(jìn)行簡單的介紹,針對這些關(guān)鍵技術(shù)的優(yōu)缺點和適用場合比較分析,提出常用的個性化推薦策略。 然后采用個案調(diào)查法,以Amazon.com、豆瓣網(wǎng)、MovieLens.org三個成功的電子商務(wù)個性化推薦系統(tǒng)為研究案例,分析他們典型的推薦功能和采用的推薦策略以及優(yōu)勢特點,從中獲取個性化推薦理論應(yīng)用的成功經(jīng)驗。 最后分析E-Learning個性化系統(tǒng)中的推薦服務(wù)形式,通過比較與電子商務(wù)推薦系統(tǒng)的相似之處找到可借鑒到E-Learning中的幾個方面:1.建立虛擬學(xué)習(xí)社區(qū);2.引入社會化標(biāo)簽,并做標(biāo)簽修正;3.充分發(fā)掘用戶之間的推薦;4.優(yōu)化推薦;5.創(chuàng)建個性化的學(xué)習(xí)環(huán)境。 最終提出E-Learning個性化系統(tǒng)的推薦策略:采用協(xié)同過濾技術(shù)與基于關(guān)聯(lián)規(guī)則的推薦相組合的推薦策略,建立一個虛擬學(xué)習(xí)社區(qū)。利用系統(tǒng)算法推薦與用戶之間推薦相結(jié)合的方式,將學(xué)習(xí)資源、學(xué)習(xí)活動、學(xué)習(xí)策略三者整合起來,向?qū)W習(xí)者推薦完整的E-Learning學(xué)習(xí)方案。
[Abstract]:E-Learning personalized recommendation system, as the most important learning method in the lifelong learning system, has received extensive attention under the background of the construction of digital lifelong learning system. Personalized recommendation system (PRS) was first applied in the field of electronic commerce and information service, and has been relatively mature. The application of PRS in E-Learning is still in the exploratory stage. In view of this, the author takes the personalized recommendation system in the field of electronic commerce as the breakthrough point, selects the successful recommendation system case to do the research, obtains the successful experience of the personalized recommendation system application. The enlightenment to the individuation construction of E-Learning system is extracted, and the recommendation strategy of E-Learning personalization system is discussed finally. This research takes the individualized recommendation theory as the basic theoretical basis. Firstly, the connotation of personalized recommendation theory is discussed by using literature research method, and the key technologies of individualized recommendation are briefly introduced, and the advantages and disadvantages of these key technologies and their applicable situations are compared and analyzed. Put forward the commonly used personalized recommendation strategy. Then using the case study method, taking Amazon.com, MovieLens.org as the research case, the typical recommendation function, the recommendation strategy and the advantages are analyzed. The successful experience of the application of personalized recommendation theory is obtained. Finally, this paper analyzes the form of recommendation service in E-Learning personalization system, and finds out several aspects of E-Learning that can be used for reference by comparing with E-commerce recommendation system. Establish a virtual learning community. Introduction of social labels, and do label correction. Fully explore the recommendation between users. Optimization recommendation 5. Create a personalized learning environment. Finally, the recommendation strategy of E-Learning personalization system is put forward: a virtual learning community is established by using collaborative filtering technology and association rule-based recommendation strategy. By using the combination of system algorithm recommendation and user recommendation, learning resources, learning activities and learning strategies are integrated to recommend a complete E-Learning learning scheme to learners.
【學(xué)位授予單位】：東北師范大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2010
【分類號】：TP391.6

【引證文獻(xiàn)】

相關(guān)博士學(xué)位論文 前1條

1 姜強(qiáng);自適應(yīng)學(xué)習(xí)系統(tǒng)支持模型與實現(xiàn)機(jī)制研究[D];東北師范大學(xué);2012年

相關(guān)碩士學(xué)位論文 前1條

1 白立廣;現(xiàn)代遠(yuǎn)程教育中學(xué)習(xí)者關(guān)系管理體系研究[D];東北師范大學(xué);2012年

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