Abstract: A computing device receives, via a user interface, a drawing input directed to a dataset of time series data. The computing device converts the drawing input into a set of search terms and executes a query against a search index for the dataset using the set of search terms to retrieve a plurality of labeled trend events. Each of the labeled trend events corresponds to a respective portion of a respective line chart of a set of line charts representing the time series data and has a respective chart identifier. The computing device generates a first subset of line charts according to the retrieved plurality of labeled trend events. The computing device displays, on the user interface, one or more line charts of the first subset of line charts.

Abstract: A computing device receives a natural language input specifying search terms directed to a dataset. The device parses the input into tokens and executes queries against a search index to retrieve a plurality of labeled trend events. Each labeled trend event has a respective chart identifier. The device determines a respective composite score for each labeled trend event and individually assigns each labeled trend event to a respective group. For each group, the device sorts the respective labeled trend events within the respective group according to respective composite scores, determines a respective final score for each group, and ranks the groups according to one or more determined final scores. The device retrieves data corresponding to a first subset of line charts having the respective chart identifiers of the ranked groups, generates the first subset of line charts, and displays one or more line charts of the first subset with annotation.

Abstract: A computing device receives a natural language input specifying search terms directed to a dataset. The device parses the input into tokens and executes queries against a search index to retrieve a plurality of labeled trend events. Each labeled trend event has a respective chart identifier. The device determines a respective composite score for each labeled trend event and individually assigns each labeled trend event to a respective group. For each group, the device sorts the respective labeled trend events within the respective group according to respective composite scores, determines a respective final score for each group, and ranks the groups according to one or more determined final scores. The device retrieves data corresponding to a first subset of line charts having the respective chart identifiers of the ranked groups, generates the first subset of line charts, and displays one or more line charts of the first subset with annotation.

Abstract: A computing device receives a natural language input specifying a first search term and a second search term, directed to a dataset. The device (i) executes, for the first search term, first queries against a search index to retrieve a first set of labeled trend events; and (ii) executes for the second search term, second queries against the search index to retrieve a second set of labeled trend events. Each labeled trend event has a respective chart identifier. The device constructs sequences of labeled trend events based on the retrieved sets of labeled trend events, assigns each sequence into groups according to the respective chart identifier, and ranks the groups. The device retrieves data corresponding to a subset of line charts having the respective chart identifiers of the ranked groups, generates the subset of line charts, and displays one or more line charts of the subset.

Abstract: Embodiments are directed to managing visualizations of data using a network computer. A modeling engine may provide a data model that includes a plurality of data objects and a display model that includes a plurality of display objects based on the plurality of data objects. Parameter action objects may be associated with display objects in the display model. In response to an activation of the parameter action objects, values associated with display objects may be assigned to the parameter associated with a parameter action object and actions associated with the parameter may be executed to modify the display model.

Abstract: Embodiments are directed to managing visualizations of data using a network computer. A modeling engine may provide a data model that includes a plurality of data objects and a display model that includes a plurality of display objects based on the plurality of data objects. Parameter action objects may be associated with display objects in the display model. In response to an activation of the parameter action objects, values associated with display objects may be assigned to the parameter associated with a parameter action object and actions associated with the parameter may be executed to modify the display model.

Abstract: Embodiments are directed to managing visualizations of data using a network computer. A modeling engine may provide a data model that includes a plurality of data objects and a display model that includes a plurality of display objects based on the plurality of data objects. Parameter action objects may be associated with display objects in the display model. In response to an activation of the parameter action objects, values associated with display objects may be assigned to the parameter associated with a parameter action object and actions associated with the parameter may be executed to modify the display model.

Abstract: Embodiments are directed to managing visualizations of data using a network computer. A modeling engine may provide a data model that includes a plurality of data objects and a display model that includes a plurality of display objects based on the plurality of data objects. Parameter action objects may be associated with display objects in the display model. In response to an activation of the parameter action objects, values associated with display objects may be assigned to the parameter associated with a parameter action object and actions associated with the parameter may be executed to modify the display model.

Abstract: Methods and apparatus are provided for accessing an experience journal which includes unstructured text items relating to a topic, such as a medical condition. The method is implemented in a computer system including a processor, a storage device, a video display unit having a display screen, and a user interface. The unstructured text items are stored in the storage device. Similarities among the unstructured text items are determined, and icons, one corresponding to each of the unstructured text items, are displayed on the display screen. The icons are positioned on the display screen relative to each other, such that the distances between icons are representative of the determined similarities among the unstructured text items. In response to user selection of one of the icons, the corresponding unstructured text item is displayed on the display screen.