Machine learning based system and method for improving false alert triggering in web based device management applications
作者： Helen Haekyung Shin , William Peter Oatman
DOI:
关键词: Alert status 、 Dynamic programming 、 Machine learning 、 Hidden Markov model 、 Web application 、 State (computer science) 、 Device status 、 Computer science 、 Artificial intelligence
摘要: Methods, systems, and processor-readable media for remotely providing a device status alert. In an example embodiment, data indicative of the one or more devices can be subject to HMM (Hidden Markov Model) dynamic programming algorithm determine latent state (or devices). A alert model trained based on such expanded with respect wide range including utilizing semi-supervised learning. The then integrated into management application that provides regarding model.
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