UGC Approved Journal no 63975(19)

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Published in:

Volume 5 Issue 11
November-2018
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIRDS06029


Registration ID:
232108

Page Number

193-198

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Title

A Survey on Machine Learning- based Translation Systems using Rule-based approach

Authors

Abstract

Abstract: Machine translation is defined as the branch of artificial intelligence which covers the task of converting a source language to any other target language from the set of natural languages. The meaning of the text should be preserved and output should be fluent as well as correct. It is one of the applications of NLP (Natural Language Processing), which is the study of interaction between human languages and the computers. It is important for the computers to read, analyze, understand and derive meaningful information from the human natural language. There are various types of machine translation available. This paper discusses them in detail.

Key Words

Keywords: NLP, Rule Based, Empirical, Machine Learning, SLR

Cite This Article

"A Survey on Machine Learning- based Translation Systems using Rule-based approach", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 11, page no.193-198, November 2018, Available :http://www.jetir.org/papers/JETIRDS06029.pdf

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2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"A Survey on Machine Learning- based Translation Systems using Rule-based approach", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 11, page no. pp193-198, November 2018, Available at : http://www.jetir.org/papers/JETIRDS06029.pdf

Publication Details

Published Paper ID: JETIRDS06029
Registration ID: 232108
Published In: Volume 5 | Issue 11 | Year November-2018
DOI (Digital Object Identifier):
Page No: 193-198
Country: -, -, - .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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