Lourens, Roger LPatra, AHassim, LuqmaanSima, FaheemMoodley, AvashlinSharma, P2019-04-012019-04-012018-12Lourens, R.L. et al. 2018. Water quality information dissemination at real-time in South Africa using language modelling. Machine Learning for the Developing World (ML4D) Workshop, part of the 23rd Conference on Neural Information Processing Systems (NIPS 2018), 8 December 2018, Palais des Congrès de Montréal, Montréal, Canadahttps://arxiv.org/abs/1812.09745http://hdl.handle.net/10204/10893Paper presented at the Machine Learning for the Developing World (ML4D) Workshop, part of the 23rd Conference on Neural Information Processing Systems (NIPS 2018), 8 December 2018, Palais des Congrès de Montréal, Montréal, CanadaWe 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.enWater qualityMachine learningLanguage modellingConference PresentationLourens, R. L., Patra, A., Hassim, L., Sima, F., Moodley, A., & Sharma, P. (2018). Water quality information dissemination at real-time in South Africa using language modelling. http://hdl.handle.net/10204/10893Lourens, Roger L, A Patra, Luqmaan Hassim, Faheem Sima, Avashlin Moodley, and P Sharma. "Water quality information dissemination at real-time in South Africa using language modelling." (2018): http://hdl.handle.net/10204/10893Lourens RL, Patra A, Hassim L, Sima F, Moodley A, Sharma P, Water quality information dissemination at real-time in South Africa using language modelling; 2018. http://hdl.handle.net/10204/10893 .TY - Conference Presentation AU - Lourens, Roger L AU - Patra, A AU - Hassim, Luqmaan AU - Sima, Faheem AU - Moodley, Avashlin AU - Sharma, P AB - 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. DA - 2018-12 DB - ResearchSpace DP - CSIR KW - Water quality KW - Machine learning KW - Language modelling LK - https://researchspace.csir.co.za PY - 2018 T1 - Water quality information dissemination at real-time in South Africa using language modelling TI - Water quality information dissemination at real-time in South Africa using language modelling UR - http://hdl.handle.net/10204/10893 ER -