• N.Rajasekhar

Here we consider the problem of finding the relative strings those are comparative to given query string. For that various similaritydistance measures can be used like total divergence to average[15],Bhattacharya coefficient[16],cosine similarity[17]jaccard coefficient[18], and Levenshtein distance[19] This problem is of great interests to a variety of applications that need a high real-time performance, such as data cleaning, query relaxation, and spellchecking. We identify existing indexes, search algorithms, filtering strategies, selectivity-estimation techniques and other work, and comment on their respective merits and limitations.. in this paper we propose several algorithms that can greatly improve the performance of existing algorithms. Second, Filtering is a standard technique for fast approximate string matching in practice. In filtering, a quick first step is used to rule out almost all positions of a text as possible starting positions for a pattern. Typically this step consists of finding the exact matches of small parts of the pattern and for that we propose consolidation of existing filtering techniques with these algorithms, and show that they should be used assembled into one smartly, since the way to do the consolidation can greatly affect the performance. We have conducted experiments on several real data sets to evaluate the proposed techniques

A Dynamic Filtering Algorithms to Search Approximate String

"A Dynamic Filtering Algorithms to Search Approximate String", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.3, Issue 7, page no.673-677, July-2016, Available :http://www.jetir.org/papers/JETIR1701793.pdf

"A Dynamic Filtering Algorithms to Search Approximate String", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.3, Issue 7, page no. pp673-677, July-2016, Available at : http://www.jetir.org/papers/JETIR1701793.pdf