scholarly journals PRIVACY PRESERVING NATURAL LANGUAGE PROCESSING IN THE CLOUD SUPPORTING SIMILARITY BASED TEXT RETRIEVAL THROUGH BLIND STORAGE.

2016 ◽  
Vol 4 (11) ◽  
pp. 2256-2260
Author(s):  
T. Thilagam. ◽  
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Text Retrieval ◽  
Privacy Preserving

scholarly journals SecureNLP: A System for Multi-Party Privacy-Preserving Natural Language Processing

2020 ◽  
Vol 15 ◽  
pp. 3709-3721 ◽  
Author(s):  
Qi Feng ◽  
Debiao He ◽  
Zhe Liu ◽  
Huaqun Wang ◽  
Kim-Kwang Raymond Choo
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Privacy Preserving

A Review and evaluation of Machine Translation methods for Lumasaaba

2020 ◽  
pp. 3-17
Author(s):  
Peter Nabende
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Machine Translation ◽  
Language Processing ◽  
Research Area ◽  
Data Driven ◽  
East African ◽  
Data Set ◽  
African Languages ◽  
Translation Methods

Natural Language Processing for under-resourced languages is now a mainstream research area. However, there are limited studies on Natural Language Processing applications for many indigenous East African languages. As a contribution to covering the current gap of knowledge, this paper focuses on evaluating the application of well-established machine translation methods for one heavily under-resourced indigenous East African language called Lumasaaba. Specifically, we review the most common machine translation methods in the context of Lumasaaba including both rule-based and data-driven methods. Then we apply a state of the art data-driven machine translation method to learn models for automating translation between Lumasaaba and English using a very limited data set of parallel sentences. Automatic evaluation results show that a transformer-based Neural Machine Translation model architecture leads to consistently better BLEU scores than the recurrent neural network-based models. Moreover, the automatically generated translations can be comprehended to a reasonable extent and are usually associated with the source language input.

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