BibTeX
@MISC{Krishna_,principal,
author = {Javvaji Vamshi Krishna and P. Prabhakar},
title = {, Principal},
year = {}
}
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Abstract
Abstract:Probabilistic String Transformation is always an important research topic in the field of natural language processing and search engine optimization, Even though various traditional approaches available for string transformation or candidate set generation, they are not efficient approaches because of its parameters, Accuracy and efficiency are the basic parameters to consider them to optimize during the generation of candidate sets or output Strings, Prior to that we consider the set of likely keywords which meets the minimum levestein distance. In this paper we are proposing an efficient Model of String transformation for Candidateset generation and Query Reformulation, we are proposing an evolutionary approach for the correction of the misspelled wordswith edit distance and index based comparison either by single character or substring. I.
Keyphrases
likely keywords probabilistic string transformation efficient model string transformation single character natural language processing wordswith edit distance query reformulation evolutionary approach candidate set important research topic basic parameter search engine optimization various traditional approach minimum levestein distance output string candidateset generation efficient approach
