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A Framework for Urdu Language Translation using LESSA
Authors: Imran Sarwar Bajwa
Abstract:Internet is one of the major sources of information for the person belonging to almost all the fields of life. Major language that is used to publish information on internet is language. This thing becomes a problem in a country like Pakistan, where Urdu is the national language. Only 10% of Pakistan mass can understand English. The reason is millions of people are deprived of precious information available on internet. This paper presents a system for translation from English to Urdu. A module LESSA is used that uses a rule based algorithm to read the input text in English language, understand it and translate it into Urdu language. The designed approach was further incorporated to translate the complete website from English language o Urdu language. An option appears in the browser to translate the webpage in a new window. The designed system will help the millions of users of internet to get benefit of the internet and approach the latest information and knowledge posted daily on internet.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1086147Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2325
 Bajwa, I.S., Choudhary, M.A. (2006) "A Rule Based System for Speech Language Context Understanding" Journal of Donghua University, (English Edition) 23 (6), pp. 39-42.
 G├│mez-Pérez Asunci├│n, Fern├índez-L├│pez Mariano, Corcho Oscar, (2004) Ontological Engineering: with examples from the areas of Knowledge Management, e-Commerce and the Semantic Web. Springer.
 Drouin Patrick. (2004) "Detection of Domain Specific Terminology Using Corpora Comparison." Proceedings of the Fourth International Conference on Language Resources.
 Bajwa, I.S., Hyder, I. (2007), "UCD-Generator - A LESSA Application for Use Case Design", Proceedings of IEEE- International Conference on Information and Emerging Technologies- ICIET, pp-182-187
 Chomsky, N. (1965) "Aspects of the Theory of Syntax. MIT Press, Cambridge, Mass, 1965.
 Chow, C., & Liu, C. (1968) "Approximating discrete probability distributions with dependence trees". IEEE Transactions on Information Theory, 1968, IT-14(3), 462-467.
 Krovetz, R., & Croft, W. B. (1992) "Lexical ambiguity and information retrieval", ACM Transactions on Information Systems, 10, 1992, pp. 115-141
 Salton, G., & McGill, M. (1995) "Introduction to Modern Information Retrieval" McGraw-Hill, New York., 1995
 Maron, M. E. & Kuhns, J. L. (1997) "On relevance, probabilistic indexing, and information retrieval" Journal of the ACM, 1997, 7, 216- 244.
 Losee, R. M. (1988) "Parameter estimation for probabilistic document retrieval models". Journal of the American Society for Information Science, 39(1), 1988, pp. 8-16.
 Imran Sarwar Bajwa, Riaz-Ul-Amin, M. Asif Naeem, Muhammad Nawaz (2006), "Web Information Mining Framework using XML Based Knowledge Representation Engine, Proceedings of 2nd International Conference on Software Engineering, 2006, Lahore, Pakistan
 J. M. Zelle and R. J. Mooney, (1993), "Learning semantic grammars with constructive inductive logic programming", in: Proceedings of the 11th National Conference on Artificial Intelligence (AAAI Press/MIT Press, Washington, D.C.) , pp. 817-822.