Highly pathogenic avian influenza (HPAI) virus can spread rapidly, resulting in high mortality and severe economic damage. To minimize the damage incurred from such diseases, it is necessary to develop technology for analysing livestock disease and predicting livestock disease propagation. In this study, we propose a novel big data analytics model using extensive volumes of livestock disease occurrence data accumulated over an extended period. In particular, we describe a sample process based on a specific scenario that elicits information that generates sequential dissemination routes of HPAI outbreaks by applying sequential pattern mining in this paper. 2015 18-19, December,
ISCC
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.