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  • 學位論文

建立在Hadoop分散式架構上的RDF儲存庫

Build RDF storage on the distributed architecture of Hadoop

指導教授 : 葉慶隆
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摘要


全球網進入了Web 2.0,所提供的協同合作服務,讓使用者在資訊消費外又能扮演提供資訊的角色。這種以社會結構為基礎的多方向溝通知是建構與管理技術,也逐漸受到數位學習、企業管理等領域的重視,探索提升該領域淺能的可能。將網路上廣大的資訊做整合,可以使的每筆資料不再是孤立的知識庫。因此語意網則是將這些異質性資料內容做整合的一項重要技術。   語意網的架構基礎是以本體知識論(Web Ontology Language,OWL)所建構而成的Resorce Description Framework(RDF)知識庫。也隨著雲端計算架構的興起,本論文嘗試在雲端的平行運算下發展語意網的分散式RDF知識庫的查詢。   我們將透過Apache Hadoop計畫發展所提供可靠的、可擴展的分散式計算架構的開放源軟體的HBase為基本儲存基底,接著以Hadoop提供的「Map-Reduce」套件提高查詢的效率。   希望藉由本次實驗所建構而成的系統及實驗數據,在雲端裡可以使分散式的知識庫平台相互結合、互通,並且可以促進遍在的個人化社交分享及協同合作服務。

關鍵字

Web 2.0 RDF HBase Hadoop

並列摘要


World Wide Web(World Wide Web ,WWW) into the Web 2.0, provides collaborative services so that users can play outside in the information provided consumer information role. This kind of social network multi-directional communication is to build knowledge and management techniques, is gradually being digital learning, business management and other areas of importance to explore the field of light can enhance the possibility. General information on the network to do the integration, each can make the knowledge base of information is no longer isolated. So the Semantic Web content sucked do these heterogeneous data integration is an important technology.   We will use Apache Hadoop project development to provide reliable, scalable, open source distributed computing software architecture as the basic storage HBase base, then to Hadoop provides the "Map-Reduce" kit to improve the efficiency of query.   Hoping that through this experiment constructed by the system and the experimental data, the clouds can make the distributed knowledge base platform to interact and exchange, and can be personalized to promote ubiquitous social sharing and collaboration services.

並列關鍵字

Web 2.0 RDF HBase Hadoop

參考文獻


[2] Tim Berners-Lee, Semantic Web road map, 1998,
[4] Linking Open Data, W3C SWEO Community Project,
[7] Resource Description Framework, http://www.w3.org/RDF/
[8] Jeffrey Dean ,Sanjay Ghemawat,” MapReduce: Simplified Data Processing
[12] Andrew Newman, Jane Hunter, Yuan-Fang Li, Chris Bouton, Melissa Davis,” A Scale-Out RDF Molecule Store for Distributed Processing of Biomedical Data”, WWW 2008, April 21--25, 2008, Beijing, China

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