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A Review on Cloud Data Mining and Data Integrity

R. Sumithra, Dr. Sujni Paul, Dr.V. Thavavel

Abstract


This paper presents a review of how data mining is used in cloud computing as discussed in various research contributions. Cloud computing has become a viable mainstream solution for data processing, storage and distribution. It promises on demand, scalable, pay-as-you-go compute and storage capacity. To analyze “big data” on clouds, it is very important to research data mining strategies based on cloud computing paradigm from both theoretical and practical views. The purpose of this paper is to study a strategy of data mining on cloud. Hadoop, one of the open source implementation of Map reduce framework is very useful in distributed data mining concepts.  While outsourcing data to the mining process in cloud environment the integrity of data should be maintained. Here a discussion is being given on cloud computing security issues and solutions as given in various research paperse�x HCHX�Uoned by many people in order to improve Web service levels and address the existing Web services requested by the people. The backbone of this solution is clearly the UDDI (private) registry. Earlier for web mining service they use WSDL-S approach, which had undergone many semantic problems. Since WSDL-S is a light weight solution approach it fails in reaching the efficiency levels of web mining service. To overcome this issue I am proposing a new solution by using OWL-S upper ontologies, which is a full solution for achieving an efficient web mining service. A matching algorithm is designed in OWL-S approach which specifies the semantic matching between a service request and a service description which does Semantic-based Web data mining by combining the semantic Web and Web mining. Software that implements a given matching algorithm is called a matchmaking engine. Practical implementation of this OWL-S approach in Semantic Web makes Web mining easier to achieve, but also can improve the effectiveness of Web mining. Here I am giving knowledge about semantic web and web mining. Finally I propose to build a semantic-based Web mining model under the framework of the Agent.

 


Keywords


Cloud Computing, Association Rule Mining, Map Reduce, Data Integrity, Outsourcing, Security Model

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References


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