String Similarity Search Using Edit Distance and Soundex Algorithm
P. Pranathi1, C. Karthikeyan2, D. Charishma3

1P.Pranathi, Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram (A.P), India.
2Dr. C. Karthikeyan, Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram (A.P), India.
3D.Charishma, Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram (A.P), India.

Manuscript received on 18 April 2019 | Revised Manuscript received on 25 April 2019 | Manuscript published on 30 April 2019 | PP: 401-405 | Volume-8 Issue-4, April 2019 | Retrieval Number: D6181048419/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: String similarity is a major inquiry that has been generally used for DNA sequencing, error tolerant, auto completion, and data cleaning which is required in database, data warehousing, and data mining. String similarity search is possible in various methodologies of procedures like Edit distance, Cosine distance, Soundex algorithm, Hamming distance and Levensntein distance, etc.., These strategies can be applied for long strings, which are not possible by the current methodologies on the grounds that the extent of the record constructed and an opportunity to manufacture such list. We apply distinctive string similitude strategies and check which procedure gives progressively suitable qualities. Our similarity measures incorporate Edit distance, Cosine similarity, Soundex algorithm, Hamming separation and Levensntein distance
Keywords: Cosine Similarity, Edit Distance, Hamming Distance, Levensntein Distance, Soundex Algorithm.

Scope of the Article: Algorithm Engineering