Janyl Jumadinova1, Oliver Bonham-Carter1, Hanzhong Zheng1,2,*, Michael Camara1, Dejie Shi3
Journal on Big Data, Vol.2, No.4, pp. 145-155, 2020, DOI:10.32604/jbd.2020.010090
- 24 December 2020
Abstract Text mining has emerged as an effective method of handling and
extracting useful information from the exponentially growing biomedical
literature and biomedical databases. We developed a novel biomedical text
mining model implemented by a multi-agent system and distributed computing
mechanism. Our distributed system, TextMed, comprises of several software
agents, where each agent uses a reinforcement learning method to update the
sentiment of relevant text from a particular set of research articles related to
specific keywords. TextMed can also operate on different physical machines to
expedite its knowledge extraction by utilizing a clustering technique. We
collected More >
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