Abstract: Information in a diagram is logically structured using lists, containers, and callouts without requiring the diagram author to explicitly define a structure or map any diagram contents to a structure. Logical relationships are inferred based on actions associated with shapes, groupings, and attributes of shapes/groupings taken by the author. Feedback mechanisms are provided to communicate an underlying structure to the author. Intelligent behaviors are enabled to expose manipulation of diagrams based on their logical structure.

Abstract: Information in a diagram is logically structured using lists, containers, and callouts without requiring the diagram author to explicitly define a structure or map any diagram contents to a structure. Logical relationships are inferred based on actions associated with shapes, groupings, and attributes of shapes/groupings taken by the author. Feedback mechanisms are provided to communicate an underlying structure to the author. Intelligent behaviors are enabled to expose manipulation of diagrams based on their logical structure.

Abstract: Information in a diagram is logically structured using lists, containers, and callouts without requiring the diagram author to explicitly define a structure or map any diagram contents to a structure. Logical relationships are inferred based on actions associated with shapes, groupings, and attributes of shapes/groupings taken by the author. Feedback mechanisms are provided to communicate an underlying structure to the author. Intelligent behaviors are enabled to expose manipulation of diagrams based on their logical structure.

Abstract: Information in a diagram is logically structured using lists, containers, and callouts without requiring the diagram author to explicitly define a structure or map any diagram contents to a structure. Logical relationships are inferred based on actions associated with shapes, groupings, and attributes of shapes/groupings taken by the author. Feedback mechanisms are provided to communicate an underlying structure to the author. Intelligent behaviors are enabled to expose manipulation of diagrams based on their logical structure.

Abstract: Information in a diagram is logically structured using lists, containers, and callouts without requiring the diagram author to explicitly define a structure or map any diagram contents to a structure. Logical relationships are inferred based on actions associated with shapes, groupings, and attributes of shapes/groupings taken by the author. Feedback mechanisms are provided to communicate an underlying structure to the author. Intelligent behaviors are enabled to expose manipulation of diagrams based on their logical structure.

Abstract: Information in a diagram is logically structured using lists, containers, and callouts without requiring the diagram author to explicitly define a structure or map any diagram contents to a structure. Logical relationships are inferred based on actions associated with shapes, groupings, and attributes of shapes/groupings taken by the author. Feedback mechanisms are provided to communicate an underlying structure to the author. Intelligent behaviors are enabled to expose manipulation of diagrams based on their logical structure.

Abstract: Customizable data diagrams are provided by a data diagram software facility. The facility receives a reference to a multidimensional data set on which to base an initial data diagram. Based, at least in part, on this information, the facility generates a data diagram providing a graphical representation of nodes corresponding to data from the multidimensional data set. The facility displays the data diagram, which can be modified by a user. For example, the facility may provide tools that allow the user to change the order of the nodes of the data diagram, change the shape of the nodes of the data diagram, change the color or format of the nodes of the data diagram, etc. The facility may also provide functionality that allows the user to drill down on aspects of the data diagram based on a breakdown scheme.

Abstract: The present invention is a segmenter used in a natural language processing system. The segmenter segments a textual input string into tokens for further natural language processing. In accordance with one feature of the invention, the segmenter includes a tokeinzer engine that proposes segmentations and submits them to a linguistic knowledge component for validation. In accordance with another feature of the invention, the segmentation system includes language specific data that contains a precedence hierarchy for punctuation. If proposed tokens in the input string contain punctuation, they can illustratively be broken into subtokens based on the precedence hierarchy.