【摘要】：近年來,由于互聯(lián)網(wǎng)不斷地深入人類社會的各個領(lǐng)域,網(wǎng)絡(luò)數(shù)據(jù)越發(fā)泛濫,從而云計算、分布式存儲等大數(shù)據(jù)處理技術(shù)快速地發(fā)展。許多云系統(tǒng)都在積極籌備、建設(shè)之中,面對日益龐大、復(fù)雜的資源池、個性化推送技術(shù)的應(yīng)用已經(jīng)變得勢在必行。教育領(lǐng)域也不例外。隨著教育信息化程度的提高,人們已逐漸不再僅僅去圖書館、書店尋找自己需要的教育資料,而是更多地通過互聯(lián)網(wǎng)絡(luò)查詢、檢索想要的數(shù)字資源。不僅如此,在線教育、公開課堂等網(wǎng)絡(luò)教育也越來越流行。而在海量的教育資源中,如何快速有效地滿足用戶的個性需求,成了“教育云”系統(tǒng)服務(wù)的重要內(nèi)容。 基于現(xiàn)狀,本文提出了一套面向?qū)W生的個性化推送方案。以滿足學生對教育資源的需求。 本文首先對分布式存儲系統(tǒng)和幾種主流的個性化推送技術(shù)進行了研究、分析,比較它們的優(yōu)缺點。接著,分析教育云系統(tǒng)的用戶群和資源池的特征,結(jié)合基于內(nèi)容的推送技術(shù)的特點,建立學生用戶與教育資源的數(shù)學模型。學生模型以學生的知識廣度、年級、成績等特征作為變量；資源模型則以教育資源的知識面、難易度等特征為變量。在建立的模型的基礎(chǔ)上,提出了一套教育云系統(tǒng)的個性化推送方案。整個推送方案包含了特征的提取、知識廣度的匹配和知識深度的匹配等主要模塊。并逐一對各模塊進行了設(shè)計、實現(xiàn)。最后,在以Hadoop集群為主體的分布式存儲平臺上,初步實現(xiàn)了這個教育云系統(tǒng)的個性化推送方案。 論文提出的個性化推送方案可以作為教育云系統(tǒng)個性化服務(wù)的組成部分,應(yīng)用于以Hadoop集群為存儲系統(tǒng)的教育平臺。
[Abstract]:In recent years, because the Internet has continuously penetrated into various fields of human society, the network data has become more and more widespread, thus big data processing technology such as cloud computing, distributed storage and so on has developed rapidly. Many cloud systems are actively preparing and building. In the face of the increasingly large and complex resource pool, the application of personalized push technology has become imperative. The field of education is no exception. With the improvement of educational informatization, people are no longer just going to the library, bookstores to find their own educational materials, but more through the Internet query, to retrieve the desired digital resources. Not only that, online education, open classroom and other network education is becoming more and more popular. In the mass of educational resources, how to meet the needs of users quickly and effectively has become an important part of educational cloud system service. Based on the present situation, this paper puts forward a set of personalized push scheme for students. To meet the needs of students for educational resources. In this paper, the distributed storage system and several popular personalized push technologies are studied, and their advantages and disadvantages are compared. Then, the characteristics of user group and resource pool of educational cloud system are analyzed, and the mathematical model of student users and educational resources is established by combining the characteristics of content-based push technology. The student model takes the characteristics of students' knowledge span, grade and achievement as variables, while the resource model takes the characteristics of educational resources, such as knowledge, difficulty and so on, as variables. Based on the established model, a personalized push scheme of educational cloud system is proposed. The whole push scheme includes feature extraction, knowledge breadth matching and knowledge depth matching. Each module is designed and realized one by one. Finally, on the distributed storage platform with Hadoop cluster as the main body, the individualized push scheme of the educational cloud system is implemented preliminarily. The personalized push scheme proposed in this paper can be used as a part of the personalized service of the educational cloud system and can be applied to the education platform with Hadoop cluster as the storage system.
【學位授予單位】：華南理工大學
【學位級別】：碩士
【學位授予年份】：2013
【分類號】：TP391.3;TP333

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