Abstract: Methods and apparatuses for generating insights for improving an organization from unstructured and structured data. Natural language processing is employed to process the aggregated data from various data sources to create topics and the features that impact the topics. These topics are then used to generate recommendations to improve customer satisfaction with the organization.

Abstract: Methods and apparatuses for generating insights for improving an organization from unstructured and structured data. Natural language processing is employed to process the aggregated data from various data sources to create topics and the features that impact the topics. These topics are then used to generate recommendations to improve customer satisfaction with the organization.

Abstract: Methods and apparatuses for generating insights for improving a health organization from unstructured and structured data. Natural language processing is employed to process the aggregated data from various data sources to create attributes and contributors. The attributes and weighted contributors are processed with business rules and/or compliance rules to form the insights.

Abstract: A method and system for displaying predictions on a spatial map includes using a data analyzer for analyzing heterogeneous data having a spatial component to find utilizable data and using machine learning to automatically extract relationships from the utilizable data. The extracted relationships are used to make a prediction about at least one location on the spatial map and present that prediction in an oblique or perspective view. An interface presents the prediction on the spatial map in the form of a heat map overlying a 3-D topographical map. Although the 3-D map can be shown as any form of graphical projection including an oblique projection or orthographic projection, preferably a perspective view is used. It is also preferred that the graphical projection be interactive. The heat map may be 2-D or 3-D and be selectively displayed depending on the preference of a user.

Abstract: A method and system for displaying predictions on a spatial map includes using a data analyzer for analyzing heterogeneous data having a spatial component to find utilizable data and using machine learning to automatically extract relationships from the utilizable data. The extracted relationships are used to make a prediction about at least one location on the spatial map and present that prediction in an oblique or perspective view. An interface presents the prediction on the spatial map in the form of a heat map overlying a 3-D topographical map. Although the 3-D map can be shown as any form of graphical projection including an oblique projection or orthographic projection, preferably a perspective view is used. It is also preferred that the graphical projection be interactive. The heat map may be 2-D or 3-D and be selectively displayed depending on the preference of a user.