Abstract: Instances of claim data are received by an apparatus. Each instance of claim data corresponds to an entity. A claim vector is generated for each instance of claim data. The claim vector is added to a group of claim vectors that all correspond to a same entity. Each group of claim vectors is aggregated to generate an entity vector corresponding to the entity. Based at least in part on the entity vector and (a) an entity profile corresponding to the corresponding entity or (b) an entity cluster with which the entity is associated, at least one behavior signal value is determined for the entity. A behavior signal is amended to include the behavior signal value. The behavior signal comprises at least two behavior signal values. Each of the behavior signal values are associated with a different time period. The behavior signal is provided for display and/or further processing.

Abstract: Embodiments of the present disclosure provide apparatuses, methods, computer program products, and systems for data perspective generation and visualization. Some example embodiments provide advantages of exploring various ideas, represented by and/or associated with one or more perspective data objects, without utilizing a complex re-configuration stage for one or more machine learning models, and/or without utilizing one or more team members conventionally required to ensure proper implementation of the idea(s). Similar advantages are obtained when desiring to change an existing idea, change the level of granularity associated with the processing, and/or the like. Some embodiments are configured to cause rendering of interfaces associated with the processing, and/or enable a user to user interaction for inputting the desired level of granularity of the generated perspectives and/or desired granularity for the analysis of the data set.

Abstract: Instances of claim data are received by an apparatus. Each instance of claim data corresponds to an entity. A claim vector is generated for each instance of claim data. The claim vector is added to a group of claim vectors that all correspond to a same entity. Each group of claim vectors is aggregated to generate an entity vector corresponding to the entity. Based at least in part on the entity vector and (a) an entity profile corresponding to the corresponding entity or (b) an entity cluster with which the entity is associated, at least one behavior signal value is determined for the entity. A behavior signal is amended to include the behavior signal value. The behavior signal comprises at least two behavior signal values. Each of the behavior signal values are associated with a different time period. The behavior signal is provided for display and/or further processing.

Abstract: Instances of claim data are received by an apparatus. Each instance of claim data corresponds to an entity. A claim vector is generated for each instance of claim data. The claim vector is added to a group of claim vectors that all correspond to a same entity. Each group of claim vectors is aggregated to generate an entity vector corresponding to the entity. Based at least in part on the entity vector and (a) an entity profile corresponding to the corresponding entity or (b) an entity cluster with which the entity is associated, at least one behavior signal value is determined for the entity. A behavior signal is amended to include the behavior signal value. The behavior signal comprises at least two behavior signal values. Each of the behavior signal values are associated with a different time period. The behavior signal is provided for display via an interactive user interface and/or further processing.

Abstract: Embodiments of the present disclosure provide apparatuses, methods, computer program products, and systems for data perspective generation and visualization. Some example embodiments provide advantages of exploring various ideas, represented by and/or associated with one or more perspective data objects, without utilizing a complex re-configuration stage for one or more machine learning models, and/or without utilizing one or more team members conventionally required to ensure proper implementation of the idea(s). Similar advantages are obtained when desiring to change an existing idea, change the level of granularity associated with the processing, and/or the like. Some embodiments are configured to cause rendering of interfaces associated with the processing, and/or enable a user to user interaction for inputting the desired level of granularity of the generated perspectives and/or desired granularity for the analysis of the data set.

Abstract: Instances of claim data are received by an apparatus. Each instance of claim data corresponds to an entity. A claim vector is generated for each instance of claim data. The claim vector is added to a group of claim vectors that all correspond to a same entity. Each group of claim vectors is aggregated to generate an entity vector corresponding to the entity. Based at least in part on the entity vector and (a) an entity profile corresponding to the corresponding entity or (b) an entity cluster with which the entity is associated, at least one behavior signal value is determined for the entity. A behavior signal is amended to include the behavior signal value. The behavior signal comprises at least two behavior signal values. Each of the behavior signal values are associated with a different time period. The behavior signal is provided for display via an interactive user interface and/or further processing.