博碩士論文 103522002 完整後設資料紀錄

DC 欄位 語言
DC.contributor資訊工程學系zh_TW
DC.creator邵盈智zh_TW
DC.creatorYingzhi Shaoen_US
dc.date.accessioned2016-7-22T07:39:07Z
dc.date.available2016-7-22T07:39:07Z
dc.date.issued2016
dc.identifier.urihttp://ir.lib.ncu.edu.tw:88/thesis/view_etd.asp?URN=103522002
dc.contributor.department資訊工程學系zh_TW
DC.description國立中央大學zh_TW
DC.descriptionNational Central Universityen_US
dc.description.abstract近年來,開放教育資源(Open Educational Resources)逐漸的普及,使用者透過網路可以針對自身得需要輕易的取得和分享教學資源,開放教育資源也開始對教師、學習者選取教學、學習資源產生影響。 然而龐大的資源數量也導致使用者需花費大量時間找尋所需資源,僅依賴搜尋引擎仍不足以滿足使用者的需求,多數的研究也顯示如何幫助使用者找到適合的資源是一個具挑戰的問題。因此本研究提出了一個使用關聯規則建構的推薦系統,透過使用教育專家建立的教育詞彙庫分析教育資源所包含的教育詞彙,利用巨量資料分析框架針對教育資源隱含之教育辭彙建立關聯規則,利用關聯規則建立每一筆教學資源的推薦,當使用者瀏覽教育資源時可以一併得知有關聯性的開放教學資源和與教材相關的時事新聞,利用推薦系統幫助使用者找到適合的開放教育資源以提升開放資源的使用率。zh_TW
dc.description.abstractIn recent years, Open Educational Resources (OER) has gradually become widespread. That OER users can easily access, make, and share educational resources according to their own needs through Internet influences on the selection of educational resources. However, a huge amount of resources has led to OER users spend a lot of time sourcing the necessary resources only with a simple search engine and lots of research point out that help users to find “right” OER is a challenge. This paper develops an OER and OER-related news recommendation system through educational corpus, association rules and Big Data analytics technique. When educators or learners browse the OER web pages, they can be aware of the relevance of OER and OER-related news easily. This study compares the recommendation system with two platforms that OER users often choose to look for OER and results show that using recommendation system can help users find resources.en_US
DC.subject開放教育資源zh_TW
DC.subject巨量資料zh_TW
DC.subject推薦系統zh_TW
DC.subject關聯規則zh_TW
DC.subjectOpen Educational Resourcesen_US
DC.subjectOERen_US
DC.subjectBig Dataen_US
DC.subjectRecommendation Systemen_US
DC.subjectAssociation rulesen_US
DC.title應用大數據分析開發教材與相關時事推薦系統zh_TW
dc.language.isozh-TWzh-TW
DC.titleApplying Big Data Analytics to Develop an Educational Material and related News Recommendation Systemen_US
DC.type博碩士論文zh_TW
DC.typethesisen_US
DC.publisherNational Central Universityen_US

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