An Advanced Precision based Approach to String Transformation
B. Sankara Babu1, K. Rajasekhar Rao2, P. Satheesh3
1B. Sankara Babu, Assistant Professor, Department of CSE, Gokaraju Rangaraju Institute of Engineering and Technology Hyderabad, India.
2Dr. K. Rajasekhar Rao, Professor, Department of CSE, Koneru Laxmaiah University Guntur, India.
3Dr. P. Satheesh, Assistant Professor, Department of CSE, Maharaj Vijayaram Gajapathiraj College of Engineering Vizianagaram, India.
Manuscript received on February 18, 2015. | Revised Manuscript received on February 27, 2015. | Manuscript published on March 05, 2015. | PP: 24-27 | Volume-5 Issue-1, March 2015. | Retrieval Number: A2517035115/2015©BEIESP
Open Access | Ethics and Policies | Cite
©The Authors. Published By: 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: Distinct obstacles occur in Natural language processing, Knowledge Engineering, Information Retrieval, Genetics Informatics, Computational molecular biology and Data Mining concerned to String Transformation. Consider an input string, the system automatically produces top k output strings referring to input string. Generally people perform various kinds of spelling errors such as misspell words accidentally while surfing the web. To circumvent such errors, this Paper propounds an advanced Precision based approach to string transformation which is very accurate. The proposed system comprises unique precision value allocated to each alphabet and these are aggregated to give the Total Precision of the particular word. Data sets are trained with the precision based approach by validating them to dictionary called the database. Misspell word precision is compared with the data sets precision and retrieves the top k nearest neighbour output strings relevant to input string. This is one of the best accurate Misspell word and sentence correction approach and experimentally proven on large data sets.
Keywords: String Transformation, Precision based Approach, Misspell words, Total Precision.