Abstract: Systems and methods for individual risk factor identification include identifying common risk factors for one or more risk targets from population data. Individuals are stratified into clusters based upon the common risk factors. A discriminability of each of the common risk factors is determined, using a processor, for a target cluster using individual data of the target cluster to provide re-ranked common risk factors as individual risk factors for the target cluster, such that the discriminability is a measure of how a risk factor discriminates its cluster from other clusters.

Abstract: Systems and methods for individual risk factor identification include identifying common risk factors for one or more risk targets from population data. Individuals are stratified into clusters based upon the common risk factors. A discriminability of each of the common risk factors is determined, using a processor, for a target cluster using individual data of the target cluster to provide re-ranked common risk factors as individual risk factors for the target cluster, such that the discriminability is a measure of how a risk factor discriminates its cluster from other clusters.

Abstract: Systems and methods for individual risk factor identification include identifying common risk factors for one or more risk targets from population data. Individuals are stratified into clusters based upon the common risk factors. A discriminability of each of the common risk factors is determined, using a processor, for a target cluster using individual data of the target cluster to provide re-ranked common risk factors as individual risk factors for the target cluster, such that the discriminability is a measure of how a risk factor discriminates its cluster from other clusters.

Abstract: Methods and apparatus are provided for multi-faceted visualization of rich text corpora. A data set comprising a plurality of entities, facets and relations is visualized by generating a visualization of a plurality of the facets in the data set, wherein the visualization indicates connections along the plurality of the facets in a single view using multi-faceted edges. The entities are instances of a particular concept, the facets are classes of entities and the relations are connections between pairs of the entities. A compound node comprises a representation of a primary entity, surrounded by representations of one or more secondary entities connected by one or more external relations. The internal relations can be represented as edges connecting two facet nodes from different compound nodes and a number of crossings of the edges can be reduced by adjusting a position order of facet nodes.

Abstract: Visualization techniques are provided for a clustered multidimensional dataset. A data set is visualized by obtaining a clustering of a multidimensional dataset comprising a plurality of entities, wherein the entities are instances of a particular concept and wherein each entity comprises a plurality of features; and generating an icon for at least one of the entities, the icon having a plurality of regions, wherein each region corresponds to one of the features of the at least one entity, and wherein a size of each region is based on a value of the corresponding feature. Each icon can convey statistical measures. A stabilized Voronoi-based icon layout algorithm is optionally employed. Icons can be embedded in a visualization of the multidimensional dataset. A hierarchical encoding scheme can be employed to encode a data cluster into the icon, such as a hierarchy of cluster, feature type and entity.

Abstract: Methods, systems, and articles of manufacture for exemplary visual analytics are provided herein. Visual analytics techniques are provided that combine pattern mining and temporal event visualization-based techniques. Visual episode query tools allow interactive specification of episode definitions and are combined with on-demand data analytics that perform pattern mining to help discover important intermediate events within an episode, and dynamic information visualization that allow interactive exploration and analysis of clinical event sequence data. The disclosed interactive visualization techniques identify events that impact outcome and how those associations change over time.

Abstract: Methods, systems, and articles of manufacture for exemplary visual analytics are provided herein. Visual analytics techniques are provided that combine pattern mining and temporal event visualization-based techniques. Visual episode query tools allow interactive specification of episode definitions and are combined with on-demand data analytics that perform pattern mining to help discover important intermediate events within an episode, and dynamic information visualization that allow interactive exploration and analysis of clinical event sequence data. The disclosed interactive visualization techniques identify events that impact outcome and how those associations change over time.

Abstract: Systems and methods for individual risk factor identification include identifying common risk factors for one or more risk targets from population data. Individuals are stratified into clusters based upon the common risk factors. A discriminability of each of the common risk factors is determined, using a processor, for a target cluster using individual data of the target cluster to provide re-ranked common risk factors as individual risk factors for the target cluster, such that the discriminability is a measure of how a risk factor discriminates its cluster from other clusters.

Abstract: Systems and methods for individual risk factor identification include identifying common risk factors for one or more risk targets from population data. Individuals are stratified into clusters based upon the common risk factors. A discriminability of each of the common risk factors is determined, using a processor, for a target cluster using individual data of the target cluster to provide re-ranked common risk factors as individual risk factors for the target cluster, such that the discriminability is a measure of how a risk factor discriminates its cluster from other clusters.

Abstract: Visualization techniques are provided for a clustered multidimensional dataset. A data set is visualized by obtaining a clustering of a multidimensional dataset comprising a plurality of entities, wherein the entities are instances of a particular concept and wherein each entity comprises a plurality of features; and generating an icon for at least one of the entities, the icon having a plurality of regions, wherein each region corresponds to one of the features of the at least one entity, and wherein a size of each region is based on a value of the corresponding feature. Each icon can convey statistical measures. A stabilized Voronoi-based icon layout algorithm is optionally employed. Icons can be embedded in a visualization of the multidimensional dataset. A hierarchical encoding scheme can be employed to encode a data cluster into the icon, such as a hierarchy of cluster, feature type and entity.

Abstract: A multifaceted visualization technique is provided for visually exploring topics in multi-relational data. A data set is visualized by obtaining the data set comprising a plurality of entities, facets and relations, wherein the entities are instances of a particular concept, the facets are classes of entities and the relations are connections between pairs of the entities; obtaining a selection of one of the facets as a topic facet, wherein entities in the topic facet are topic entities, wherein facets in the plurality of facets other than the topic facet are keyword facets; generating a visualization comprising the topic entities rendered as nodes arranged within a central region; and generating one or more surrounding shapes around the central region, wherein each of the surrounding shapes corresponds to one of the keyword facets, wherein entities within the corresponding keyword facet of a given one of the surrounding shapes are rendered as keyword entities.

Abstract: Methods and apparatus are provided for multi-faceted visualization of rich text corpora. A data set comprising a plurality of entities, facets and relations is visualized by generating a visualization of a plurality of the facets in the data set, wherein the visualization indicates connections along the plurality of the facets in a single view using multi-faceted edges. The entities are instances of a particular concept, the facets are classes of entities and the relations are connections between pairs of the entities. A compound node comprises a representation of a primary entity, surrounded by representations of one or more secondary entities connected by one or more external relations. The internal relations can be represented as edges connecting two facet nodes from different compound nodes and a number of crossings of the edges can be reduced by adjusting a position order of facet nodes.

Abstract: Methods and apparatus are disclosed for generating animated treemaps, such as Voronoi treemaps, to visualize dynamic hierarchical data. Changes in data are displayed using a treemap, by obtaining a multi-level tessellation having a plurality of regions as an initial state (obtained, for example, during an initialization phase); and iteratively processing the multi-level tessellation to update one or more of a region size and a centroid location of a plurality of the regions, where the multi-level tessellation is processed over substantially all levels to produce a substantially complete multi-level tessellation for each iteration. The region size is updated, for example, to correspond to one or more changing data values in the hierarchical data.

Abstract: Methods and apparatus are provided for recommending one or more concepts related to a current analytic activity of a user. One or more concepts related to a current analytic activity of a user are recommended by maintaining a logical record of analytic activity of the user by recording one or more visual analytic actions performed by a user; generating a context model for a plurality of the existing notes containing the concepts, wherein the context model for a given existing note represents information interests of the user; determining a weight for each of the plurality of concepts, wherein a given weight characterizes a relevance of a corresponding concept to the current analytic activity; and recommending one or more concepts based on the determined weight. The weight for a given concept is based on the context model for the given concept and a context model for the current analytic activity.

Abstract: Methods and apparatus are provided for recommending one or more existing notes related to a current analytic activity of a user. One or more existing notes related to a current analytic activity of a user are recommended by maintaining a logical record of analytic activity of the user by recording one or more visual analytic actions performed by a user; generating a context model for a plurality of the existing notes, wherein the context model for a given existing note represents information interests of the user; determining a relevance score for each of the plurality of existing notes, wherein a given relevance score characterizes a relevance of a corresponding existing note to the current analytic activity; and recommending one or more existing notes based on the determined relevance scores. The context model for the given existing note represents the information interests of the user at a time surrounding the point when the user recorded the corresponding existing note.

Abstract: Methods and apparatus are provided for intelligent exploratory visualization and analysis. A semantics-based client-server application architecture is provided that enables interactive visualization and analysis applications over the web. From the client perspective, user activities are observed and the client determines if a sequence of user activities comprises one or more predefined semantics-based user actions. Semantics-based action descriptor are then sent to the server, optionally with any related parameters, and a response is then received from the server. From the server perspective, one or more semantics-based action descriptors are received from the client with an action type selected from a predefined set of types, wherein the semantics-based action descriptors are based on a sequence of activities of a user. The server processes the semantics-based action descriptors and sends a response to the client in response to the one or more semantics-based action descriptors.

Abstract: Generally, methods and apparatus are provided for obtaining a user's insight provenance. A logical record of visual analytic activity of a user is maintained by recording one or more visual analytic actions. An exemplary method determines a set of action features of the one or more visual analytic actions; instantiates a data structure to record the action features; calculates a set of operations required to update the logical record based on the determined features; and updates the logical record based on the calculated operations. The visual analytic actions can optionally be classified using a predefined action taxonomy and by recording other action features. A plurality of the data structures can be associated with a node in a trail graph that represents one or more analytical paths of the user.

Abstract: Methods and apparatus are disclosed for dynamically recommending one or more visualizations for a given task based on user behavior, such as a user's interaction pattern with a current visualization. An alternate visualization type is provided to a user by observing actions of the user with a current visualization type; determining if one or more predefined action patterns is detected in the observed actions, wherein at least one of the predefined action patterns has a predefined associated alternate visualization type; and providing the alternate visualization type to the user when the associated predefined action pattern is detected. The one or more predefined action patterns may be defined by one or more rules or an example-based method.