Title

Predicting correctness of “Google translate”

Authors

Yulia Rossikova, Kean University
J. Jenny Li, Kean University
Patricia Morreale, Kean University

Document Type

Conference Proceeding

Publication Date

1-1-2019

Abstract

This paper presents a new modeless approach for Machine Learning predictions, called Radius of Neighbors (RN). We applied RN to predict the correctness of Google translator and found it to be an improvement over K-Nearest Neighbors (KNN) in terms of prediction accuracy. Both methods are applicable to situations when a mathematical prediction model does not exist or is unknown. With RN, we will be able to create new applications that rely on the users' awareness of translation accuracy, e.g. an online instant messager, which allows users to chat in various natural languages.

Publication Title

Proceedings of the 2015 International Conference on Artificial Intelligence, ICAI 2015 - WORLDCOMP 2015

First Page Number

825

Last Page Number

826

Recommended Citation

Rossikova, Yulia; Jenny Li, J.; and Morreale, Patricia, "Predicting correctness of “Google translate”" (2019). Kean Publications. 1435.
https://digitalcommons.kean.edu/keanpublications/1435