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Study on fusion technology of cloud platform based on Ontology

Author: WangWenBo
Tutor: ZhouLiJuan
School: Capital Normal University
Course: Theory of computer software
Keywords: Cloud Computing Body fusion hadoop cloud platform OWL language
CLC: TP391.1
Type: Master's thesis
Year: 2013
Downloads: 20
Quote: 0
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Abstract


Big Data era heralded the arrival of the wave of new wave of productivity growth and consumer surplus. Prospects of big data and cloud computing, networking and mobile Internet are inseparable. Form of cloud computing, data filtering process, to extract useful information, has become an important research direction of data mining.Body for a long time, has been the research goal is to use the idea of the body, giving scientific data unified, standardized semantic information, semantic level integration of heterogeneous scientific databases, making scientific database to better sharing and interoperability, This is a scientific database system management data to enhance an effective way to manage knowledge ". This paper first introduces the the body fusion research significance and research status of several existing body fusion algorithm, on the basis of several body at home and abroad fusion technology, and contrast these types of body build and integration methods advantages and disadvantages, and in which the fusion algorithm based on statistics, and the use of Hadoop cloud platform the MapReduce programming to distributed processing. Through the analysis of large amounts of data, we can get more valuable information to solve the problem of how to analyze such large-scale data. Improve the read and write speeds for the problem of slow read and write speeds, distributed storage (HDFS). By way of store redundant data against hardware failure to resolve.Able to achieve fault-tolerant software instead of hardware fault tolerance.The content of this article include the following aspects:1. For ontology integration, explores the automatic integration cloud platform-based multi-body model and method, intends to Hadoop open source cloud platform as a basis, HDFS achieve the storage, analysis implemented by Hadoop’s MapReduce programming.2. To develop the integration of storage management mechanism of the concept of space and maintenance strategy. Will use the the Hadoop components of ZooKeeper configuration maintenance, name services, distributed synchronization group, which will be responsible for scheduling the generation and integration process of the body. The same time, the body language expressed in the cloud platform and redefinition to use HBase distributed data. 3. Designed and implemented the automatic integration platform based on the body of the cloud platform, this platform enables the body to re-representation of the cloud platform and be capable of make similar body intelligence fusion effect, which can solve the problem of heterogeneous part of the body.4. The quality of the integration of the concept of space results evaluation. As Ganglia cluster monitoring tools, see load balancing, and monitoring and analysis of computer cluster, including node grid and cloud computing environments running status information, in order to observe the stability of the applicability of the system. Also need to translate the surface by the correctness of the OWL language View fusion.

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