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MULTISCALE, HIERARCHICAL CLUSTERING ON CUSTOMER OBSERVABLES USING PERSISTENT GEOMETRIC FEATURES OF CO-OCCURRENCE SIMPLICIAL COMPLEXES
MULTISCALE, HIERARCHICAL CLUSTERING ON CUSTOMER OBSERVABLES USING PERSISTENT GEOMETRIC FEATURES OF CO-OCCURRENCE SIMPLICIAL COMPLEXES
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机译：MultiScale，使用持久的几何特征在客户可观察到的同型外观复合物
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摘要
Described is a system for extracting multi-scale hierarchical clustering on customer observables (COs) data in a vehicle. The system selects a parameter for a set of incident data of COs data. Simplicial complexes are generated from the COs data based on the selected parameter. Face networks are generated from the simplicial complexes. For each face network, a set of connected components is extracted. Each connected component is transformed to a cluster of related COs, resulting in a first extracted relation between COs. The first extracted relation is used to automatically generate an alert at a client device when a second extracted relation different from the first extracted relation results from the transformation.
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