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User Profile Tracking by Web Usage Mining in Cloud Computing

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Bibliographic Details
Title: User Profile Tracking by Web Usage Mining in Cloud Computing
Authors: John, Joan M., Mini, G. Venifa, Arun, E.
Source: Procedia Engineering. Sep2012, Vol. 38, p3270-3277. 8p.
Subjects: Web analytics, Cloud computing, Information sharing, Internet content, Scalability, Databases, Distributed computing, Algorithms
Abstract: Abstract: Service oriented domain like cloud computing, composite service selection is hard to accomplish in an effective manner. The high scalability of distributed systems, and large transaction of data bases, it is a vital important to categorizes the efficient methods for distributed mining. Researcher on web has given a great attention to web usage mining which is an evolution of internet to evaluate user profiles and knowledge sharing of web content. This paper discloses the efficient relationship between the local and global transaction data items. It extracts valuable information from the large amount of data available in the user web sessions. To segment the data, the distance between the two user sessions is measured with the help of similarity distance measures. Aim of this paper is to introduce a technique called registry federation mechanism to meet the associated business requirements and it also describes a distributed algorithm for sequential mining within registry federation. [Copyright &y& Elsevier]
Copyright of Procedia Engineering is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
FullText Text:
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DbLabel: Engineering Source
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PubType: Academic Journal
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  Data: <searchLink fieldCode="JN" term="%22Procedia+Engineering%22">Procedia Engineering</searchLink>. Sep2012, Vol. 38, p3270-3277. 8p.
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  Data: <searchLink fieldCode="DE" term="%22Web+analytics%22">Web analytics</searchLink><br /><searchLink fieldCode="DE" term="%22Cloud+computing%22">Cloud computing</searchLink><br /><searchLink fieldCode="DE" term="%22Information+sharing%22">Information sharing</searchLink><br /><searchLink fieldCode="DE" term="%22Internet+content%22">Internet content</searchLink><br /><searchLink fieldCode="DE" term="%22Scalability%22">Scalability</searchLink><br /><searchLink fieldCode="DE" term="%22Databases%22">Databases</searchLink><br /><searchLink fieldCode="DE" term="%22Distributed+computing%22">Distributed computing</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink>
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  Data: Abstract: Service oriented domain like cloud computing, composite service selection is hard to accomplish in an effective manner. The high scalability of distributed systems, and large transaction of data bases, it is a vital important to categorizes the efficient methods for distributed mining. Researcher on web has given a great attention to web usage mining which is an evolution of internet to evaluate user profiles and knowledge sharing of web content. This paper discloses the efficient relationship between the local and global transaction data items. It extracts valuable information from the large amount of data available in the user web sessions. To segment the data, the distance between the two user sessions is measured with the help of similarity distance measures. Aim of this paper is to introduce a technique called registry federation mechanism to meet the associated business requirements and it also describes a distributed algorithm for sequential mining within registry federation. [Copyright &y& Elsevier]
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  Data: <i>Copyright of Procedia Engineering is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1016/j.proeng.2012.06.378
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        Text: English
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        Type: general
      – SubjectFull: Cloud computing
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      – SubjectFull: Information sharing
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      – SubjectFull: Internet content
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      – SubjectFull: Scalability
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      – SubjectFull: Databases
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      – SubjectFull: Distributed computing
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      – SubjectFull: Algorithms
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              Text: Sep2012
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