Water quality information dissemination at real-time in South Africa using language modelling
Domaine:
natural language processingenvironment and energyType de record:
paper
Créateur:
LouPatHasSim
Éditeur:
Hôte:
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. Accepted at the Machine Learning for the Developing World (ML4D) Workshop, NeurIPS 2018
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