Water quality information dissemination at real-time in South Africa using language modelling
Computers and Society
2018-12-27 v1
Abstract
We present a conversational model to apprise users with limited access to computational resources about water quality and real-time accessibility for a given location. We used natural language understanding through neural embedding driven approaches. This was integrated with a chatbot interface to accept user queries and decide on action output based on entity recognition from such input query and online information from standard databases and governmental and non-governmental resources. We present results of attempts made for some South African use cases, and demonstrate utility for information search and dissemination at a local level.
Keywords
Cite
@article{arxiv.1812.09745,
title = {Water quality information dissemination at real-time in South Africa using language modelling},
author = {Laing Lourens and Arijit Patra and Luqmaan Hassim and Faheem Sima and Avashlin Moodley and Pulkit Sharma},
journal= {arXiv preprint arXiv:1812.09745},
year = {2018}
}
Comments
Accepted at the Machine Learning for the Developing World (ML4D) Workshop, NeurIPS 2018