Abstract: The present disclosure relates clustering similar data records together in a hierarchical clustering scheme. Each tier in a cluster corresponds to a minimal match score, which reflects a degree of confidence. In this respect, a higher confidence may lead to smaller sized clusters while a lower confidence may lead to larger sized clusters. Ordinal classification may be used to generate hierarchical clusters. In some embodiments, hierarchical clustering with conflict resolution is used to resolve user-defined hard conflicts in each tier of the clustering results.

Abstract: The present disclosure relates clustering similar data records together in a hierarchical clustering scheme. Each tier in a cluster corresponds to a minimal match score, which reflects a degree of confidence. A hierarchical cluster ID is generated for respective data records. The hierarchical cluster ID may be made up of a series of values, wherein each value reflects a tier within the hierarchical clustering scheme. A user may enter a partial hierarchical cluster ID to select clusters associated with a lower confidence. Thus, in some embodiments, the hierarchical cluster ID is variable in length in a manner that corresponds to the tiers in the hierarchical clustering scheme.

Abstract: The present disclosure relates clustering similar data records together in a hierarchical clustering scheme. Each tier in a cluster corresponds to a minimal match score, which reflects a degree of confidence. In this respect, a higher confidence may lead to smaller sized clusters while a lower confidence may lead to larger sized clusters. Ordinal classification may be used to generate hierarchical clusters. In some embodiments, hierarchical clustering with conflict resolution is used to resolve user-defined hard conflicts in each tier of the clustering results.

Abstract: The present disclosure relates clustering similar data records together in a hierarchical clustering scheme. Each tier in a cluster corresponds to a minimal match score, which reflects a degree of confidence. A hierarchical cluster ID is generated for respective data records. The hierarchical cluster ID may be made up of a series of values, wherein each value reflects a tier within the hierarchical clustering scheme. A user may enter a partial hierarchical cluster ID to select clusters associated with a lower confidence. Thus, in some embodiments, the hierarchical cluster ID is variable in length in a manner that corresponds to the tiers in the hierarchical clustering scheme.

Abstract: The present disclosure relates clustering similar data records together in a hierarchical clustering scheme. Each tier in a cluster corresponds to a minimal match score, which reflects a degree of confidence. A hierarchical cluster ID is generated for respective data records. The hierarchical cluster ID may be made up of a series of values, wherein each value reflects a tier within the hierarchical clustering scheme. A user may enter a partial hierarchical cluster ID to select clusters associated with a lower confidence. Thus, in some embodiments, the hierarchical cluster ID is variable in length in a manner that corresponds to the tiers in the hierarchical clustering scheme.

Abstract: The present disclosure relates clustering similar data records together in a hierarchical clustering scheme. Each tier in a cluster corresponds to a minimal match score, which reflects a degree of confidence. In this respect, a higher confidence may lead to smaller sized clusters while a lower confidence may lead to larger sized clusters. Ordinal classification may be used to generate hierarchical clusters. In some embodiments, hierarchical clustering with conflict resolution is used to resolve user-defined hard conflicts in each tier of the clustering results.