International Business Machines Corporation

David Haim Gotz

Jimeng Sun

Jianying Hu

Nan Cao

Pei-Yun S Hsueh

Adam Perer

Zhiyuan Zhang

Krist Wongsuphasawat

Wen-Huang Cheng

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.

Identifying group and individual-level risk factors via risk-driven patient stratification

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. The compound nodes can optionally be rotated based on, for example, a global spring force model to reduce an average length of one or more of the edges and/or to allow edge bundling.

Multi-faceted visualization of rich text corpora

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.

Visual analysis of multidimensional clusters

Techniques for locating information in a document relevant to an interest of a user are provided. Information defined by the user of a document browser is collected. A context model is generated using the collected information. A document selected by the user is obtained. The document is divided into one or more segments. A relevance value is computed for each of the one or more segments by comparing each of the one or more segments to the context model. The relevance value represents a relationship to an interest of the user. Each of the one or more segments with the computed relevance value is presented in a defined organizational area of a display. The one or more segments presented on the display are linked to a corresponding one or more segments in the document.

Context-based document unit recommendation for sensemaking tasks

Methods and apparatus are provided for iterative refinement of cohorts using visual exploration and data analytics. A cohort comprised of multiple data objects is defined by obtaining an initial cohort seeding; visualizing the initial cohort using a selected view to present a current cohort; reducing the current cohort using one or more visual filters; visualizing the current cohort using a selected view; expanding the current cohort using one or more selected analytics; and determining whether the current cohort should be further modified using one or more of additional reductions and additional expansions. Cohorts can be passed between views and analytics via drag-and-drop interactions as an analysis unfolds.

Iterative refinement of cohorts using visual exploration and data analytics

Methods are provided for assisting in the organization of information accessed through a web browser. At least one item of information accessed through the web browser is captured and visually represented in a defined organizational area of a display. A relevance index is calculated for each item of information that is visually represented to a current web-browsing behavior. The relevance index is conveyed for each item of information to the current web-browsing behavior to a user of the web browser.

Methods for organizing information accessed through a web browser

Methods and apparatus are disclosed for generating animated treemaps, such as Voronoi treemaps, with node insertion to visualize dynamic hierarchical data. A treemap is processed by obtaining a multi-level tessellation having a plurality of existing regions; and inserting at least one new region into the multi-level tessellation by adjusting one or more of a size and location of at least one of the existing regions. In this manner, a stability of the treemap is preserved. The insertion selects a vertex of the multi-level tessellation as an insertion point. The selected vertex can be selected randomly from a set of vertices that define regions that are siblings to the newly inserted region; or can be a known location. A weight can be assigned to a new Voronoi generator, such as a nominal weight according to one or more constraints of the tessellation.

Generating animated voronoi treemaps to visualize dynamic hierarchical data with node insertion

Methods and apparatus are provided for interactive visualization of temporal event data and correlated outcomes. The temporal event data comprises a plurality of entities undergoing one or more events. The temporal event data is aggregated and a flow graph is generated to represent the aggregated temporal event data. The flow graph comprises a directed acyclic graph having a plurality of nodes connected by edges, wherein each of the nodes represents a group of entities in a given state. A view of the flow graph is generated and then a visualization of the flow graph view can be rendered to a user. The user can interact with the flow graph view and the visualization and/or the flow graph view can be updated based on the user interactions. The flow graph is sliced into layers, wherein a given layer i contains all nodes with i events.

Interactive visualization of temporal event data and correlated outcomes

Apparatus and articles of manufacture are provided for assisting in the organization of information accessed through a web browser. At least one item of information accessed through the web browser is captured and visually represented in a defined organizational area of a display. A relevance index is calculated for each item of information that is visually represented to a current web-browsing behavior. The relevance index is conveyed for each item of information to the current web-browsing behavior to a user of the web browser.

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Purdys, NY, United States of America

David Haim Gotz