Abstract: Embodiments of the present disclosure relate to a data analysis system that may automatically generate memory-efficient clustered data structures, automatically analyze those clustered data structures, automatically tag and group those clustered data structures, and provide results of the automated analysis and grouping in an optimized way to an analyst. The automated analysis of the clustered data structures (also referred to herein as data clusters) may include an automated application of various criteria or rules so as to generate a tiled display of the groups of related data clusters such that the analyst may quickly and efficiently evaluate the groups of data clusters. In particular, the groups of data clusters may be dynamically re-grouped and/or filtered in an interactive user interface so as to enable an analyst to quickly navigate among information associated with various groups of data clusters and efficiently evaluate those data clusters in the context of, for example, a fraud investigation.

Abstract: Embodiments of the present disclosure relate to a data analysis system that may automatically generate memory-efficient clustered data structures, automatically analyze those clustered data structures, automatically tag and group those clustered data structures, and provide results of the automated analysis and grouping in an optimized way to an analyst. The automated analysis of the clustered data structures (also referred to herein as data clusters) may include an automated application of various criteria or rules so as to generate a tiled display of the groups of related data clusters such that the analyst may quickly and efficiently evaluate the groups of data clusters. In particular, the groups of data clusters may be dynamically re-grouped and/or filtered in an interactive user interface so as to enable an analyst to quickly navigate among information associated with various groups of data clusters and efficiently evaluate those data clusters in the context of, for example, a fraud investigation.

Abstract: Embodiments of the present disclosure relate to a data analysis system that may automatically generate memory-efficient clustered data structures, automatically analyze those clustered data structures, automatically tag and group those clustered data structures, and provide results of the automated analysis and grouping in an optimized way to an analyst. The automated analysis of the clustered data structures (also referred to herein as data clusters) may include an automated application of various criteria or rules so as to generate a tiled display of the groups of related data clusters such that the analyst may quickly and efficiently evaluate the groups of data clusters. In particular, the groups of data clusters may be dynamically re-grouped and/or filtered in an interactive user interface so as to enable an analyst to quickly navigate among information associated with various groups of data clusters and efficiently evaluate those data clusters in the context of, for example, a fraud investigation.

Abstract: Systems and methods are disclosed for news events detection and visualization. In accordance with one implementation, a method is provided for news events detection and visualization. The method includes, for example, obtaining one or more documents, the one or more documents being grouped into one or more clusters having a score, and the one or more clusters being grouped into one or more megaclusters, presenting information associated with the one or more documents on one or more timelines, wherein the one or more documents are grouped into different megaclusters being presented in a visually distinct way, and filtering the presented information based on the scores associated with the one or more clusters.

Abstract: Systems, methods, and non-transitory computer readable media are provided for presenting a user interface for fault analysis. Fault information may be accessed. The fault information may identify faults for one or more machines. A fault analysis interface may be provided. The fault analysis interface may include an organization view, an instance view, a subsystem view, or a map view. The fault analysis interface may enable presentation of the organization view, the instance view, the subsystem view, and the map view. The fault analysis interface may display correlations of the faults using visuals and spatial locations of the visuals.

Abstract: Systems, methods, and non-transitory computer readable media are provided for presenting a user interface for fault analysis. Fault information may be accessed. The fault information may identify faults for one or more machines. A fault analysis interface may be provided. The fault analysis interface may include an organization view, an instance view, a subsystem view, or a map view. The fault analysis interface may enable presentation of the organization view, the instance view, the subsystem view, and the map view. The fault analysis interface may display correlations of the faults using visuals and spatial locations of the visuals.