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The web has been continuously growing and getting hourglass shape. The indexed web is measured to contain at least 30 billion pages. It is no surprise that searching data poses serious challenges in terms of quality and speed. Another important subtask of the pattern discovery process is sting matching, where in which the pattern occurrence is already known and we need determine how often and where it is occurs in given text. The target of current research challenges and identified the new trends i.e distributed environment where in which the given text file is divided into subparts and distributed to N no. of processors organized in hypercube networked fashion .To improve the search speed and reduce the time complexity we need to run the string matching algorithms in parallel distributed environment called as hypercube networked model using RMI method. we considered both KV-KMP and KV-boyer-moore string matching algorithms for pattern matching in large text data bases using three data sets and graph’s drawn for different patterns.
Assoc. Prof. Ksmvkumar. 2013. \u201cOverlapped Text Partition Algorithm for Pattern Matching on Hypercube Networked Model\u201d. Global Journal of Computer Science and Technology - E: Network, Web & Security GJCST-E Volume 13 (GJCST Volume 13 Issue E4): .
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
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Total Score: 103
Country: India
Subject: Global Journal of Computer Science and Technology - E: Network, Web & Security
Authors: Assoc. Prof. Ksmvkumar, Prof. S. Viswanadha Raju, Prof. A .Govardhan (PhD/Dr. count: 0)
View Count (all-time): 251
Total Views (Real + Logic): 9743
Total Downloads (simulated): 2629
Publish Date: 2013 04, Thu
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The web has been continuously growing and getting hourglass shape. The indexed web is measured to contain at least 30 billion pages. It is no surprise that searching data poses serious challenges in terms of quality and speed. Another important subtask of the pattern discovery process is sting matching, where in which the pattern occurrence is already known and we need determine how often and where it is occurs in given text. The target of current research challenges and identified the new trends i.e distributed environment where in which the given text file is divided into subparts and distributed to N no. of processors organized in hypercube networked fashion .To improve the search speed and reduce the time complexity we need to run the string matching algorithms in parallel distributed environment called as hypercube networked model using RMI method. we considered both KV-KMP and KV-boyer-moore string matching algorithms for pattern matching in large text data bases using three data sets and graph’s drawn for different patterns.
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