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Venkata Rao, K.
- A Partial Ratio and Ratio Based Fuzzy-Wuzzy Procedure for Characteristic Mining of Mathematical Formulas from Documents
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Authors
Affiliations
1 Department of Computer Science and Engineering, GITAM Institute of Technology, IN
2 Department of Information Technology, Anil Neerukonda Institute of Technology and Sciences, IN
3 Department of Computer Science and Systems Engineering, Andhra University, IN
1 Department of Computer Science and Engineering, GITAM Institute of Technology, IN
2 Department of Information Technology, Anil Neerukonda Institute of Technology and Sciences, IN
3 Department of Computer Science and Systems Engineering, Andhra University, IN
Source
ICTACT Journal on Soft Computing, Vol 8, No 4 (2018), Pagination: 1728-1732Abstract
Retrieval of mathematical text from data is a key predicament in present circumstances. To achieve this, we have considered three different algorithms viz., Sequence matcher, Levenshtein Distance and Fuzzy-Wuzzy. Two different variants of Fuzzy-Wuzzy are found applicable to this study out of four variants. Performance of these variants in retrieving mathematical texts, is calculated using efficiency measure, sensitivity analysis and time series exploration. Fuzzy-Wuzzy partial ratio algorithm scored better over the other variants on efficiency measure and sensitivity analysis.Keywords
Sequence Matcher, Levenshtein Distance, Fuzzy-Wuzzy, Partial Ratio.
References
- Kai Ma, Siu Cheung Hui and Kuiyu Chang, “Feature Extraction and Clustering-based Retrieval for Mathematical Formulas, Proceedings of 2nd International Conference on Software Engineering and Data Mining, pp. 372-377, 2010.
- Sidath Harshanath Samarasinghe and Siu Cheung Hui, “Mathematical Document Retrieval for Problem Solving”, Proceedings of International Conference on Computer Engineering and Technology, pp. 583-587, 2009.
- J. Misutka and L. Galambos, “Mathematical Extension of Full Text Search Engine Indexer”, Proceedings of 3rd International Conference on Information and Communication Technologies: From Theory to Applications, pp. 1-6, 2008.
- B.R. Miller and A. Youssef, “Technical Aspects of the Digital Library of Mathematical Functions”, Annals of Mathematics and Artificial Intelligence, pp. 121-136, 2003.
- H. Zhang and M.S. Lin, “An Evolutionary K-means Algorithm for Clustering Time Series Data”, Proceedings of International Conference on Machine Learning and Cybernetics, pp. 1282-1287, 2004.
- M. Kohlhase. “Markup for Mathematical Knowledge”, Proceedings of an Open Markup format for Mathematical Documents, pp. 13-23, 2006.
- G. Appa Rao, K. Venkata Rao, P.V.G.D. Prasad Reddy and T. Lava Kumar, “An Efficient Procedure for Characteristic Mining of Mathematical Formulas from Document”, International Journal of Engineering Science and Technology, Vol. 10, No. 3, pp. 152-157, 2018.
- G. Appa Rao, G. Srinivas, K. Venkata Rao and P.V.G.D. Prasad Reddy, “Characteristic Mining of Mathematical Formulas from Document-A Comparative Study on Sequence Matcher and Levenshtein Distance Procedure”, International Journal of Computer Sciences and Engineering, Vol. 6, No. 4, pp. 400-403, 2018.