Apparatus, method and computer-implemented program for editable categorization   

Abstract: The information appliance displays content in a visually perceptible grid from which the user selects a target content and upon selection of the processor automatically identifies related content each with an associated relatedness score. Movement by the user of the target content causes the related content to move and follow the target content as if attracted by an invisible spring force or tensile force. The system thus presents the user with a graphical representation of moving items of content which are attracted to the related content based on the degree of relatedness. In this way the user quickly learns how to control selection and organization of related content by mimicking movement of physical objects acting under kinematic forces that mimic natural objects.

The present disclosure relates generally to organization, categorization and extraction of computerized content, including computerized images, data and icons. More particularly the present disclosure relates to computer-implemented technology to assist a user in extracting and reorganizing desired content using a graphical user interface that models content as computer-generated physical objects in display space having kinematic properties that map to content relatedness properties. The system associates relatedness between targeted content and other content with a computer-generated physical parameter.

Computerized content can take many forms. In photographic applications the content is typically stored as raw image data files or as compressed image files (e.g., jpg format). In video applications the content is typically stored as a collection of image frames encoded using a suitable CODEC (e.g., mpeg format). Text applications may store content as generic text files, as application-specific files (e.g., Microsoft Word doc or docx format), or as printable files (e.g., pdf). Some applications store content comprising both text and image data. Examples include presentation software applications (e.g. Microsoft PowerPoint). Database applications typically store text and numeric data, and sometimes also image data according to a predefined data structure that assigns meaning to the stored data. Icon organizing and editing applications store icons as image data, in some cases with additional metadata.

When a user wishes to organize, categorize and extract content from a software system, such as those identified above or others, the process has heretofore been tedious and far from intuitive. Typically the software system requires the user to interact with a complex system of menus, dialog boxes or commands to achieve a desired content selection. Where the content includes a lot of non-text content, such as photographs, images, movies and the like, interaction becomes even more difficult because text searching techniques are not highly effective and may not even be available

Where the content data store is large, such as with a large collection of stored photographic images, the task of organizing, categorizing and extracting desired content can be quite daunting. There are some automated tools that can be used to categorize image content, based on image characteristic extraction, face/object recognition, and the like. However, these tools often retrieve too many hits, many of which the user must then manually reject.

SUMMARY

The disclosed system associates relatedness between targeted content and other content with a physical parameter. In this way, the disclosed system provides a user-friendly, natural way for a user to organize, categorize and extract content from a data store, such as a data store of digitized images or other visual content.

The system maps content relatedness (degree of relationship) onto computer-generated physical object properties. In the computer-generated display space, the items of content are depicted as moveable objects to which the physical object properties are associated. Using a suitable touch gesture, or pointing device selection operation, the user can select and move a desired item of content. In so doing, other related items of content move as if attracted to the selected content by an invisible attractive force (e.g., invisible spring force, invisible gravitational force, or other kind of force). Thus by dragging a selected content item, the items of related content will follow, exhibiting kinematic motion as if they were physical objects acted upon by the invisible attractive force, where the degree of relatedness defines the strength of that force. Thus strongly related contents are attracted by a stronger force than less related content. Thus by simply watching the content movement the user can tell how closely the content items relate to the selected content.

Because relatedness is mapped onto the computer-generated force, more strongly related items move more quickly towards the selected content, thereby causing the related content to naturally cluster with the most closely related content lying closer to the selected content than the less closely related content.

Although rendered in computer-generated display space, the selected item of content, and those related to it, move as if mimicking the behavior physical objects. The user thus learns quite quickly and naturally how to organize, categorize and extract content, simply by touch and drag or (click and drag) movements.

A general concept is to use some kind of physical parameter to represent the relatedness between targeted content and other contents. Examples of such physical parameters include but are not limited to: (a) force acting between related content (or icons) and targeted content (or icons), such as tensile force and/or attractive force; (b) speed with which related content (or icons) come close to targeted content (or icons); (c) final relative position of related content (or icons) to final position of targeted content (or icons); and combinations thereof.

Further areas of applicability will become apparent from the description provided herein. The description and specific examples in this summary are intended for purposes of illustration only and are not intended to limit the scope of the present disclosure.

The drawings described herein are for illustrative purposes only of selected embodiments and not all possible implementations, and are not intended to limit the scope of the present disclosure.

FIG. 1 is a plan view of an exemplary information appliance, illustrating how the user organizes, categorizes and extracts content;

FIG. 2 is a schematic block diagram of a computer hardware implementation of the information appliance of FIG. 1;

FIG. 3 is a user interface diagram, illustrating in greater detail the user interface components of the information appliance of FIG. 1;

FIG. 4a is a detailed user interface diagram, showing the grid component of the user interface of FIG. 3 and illustrating how items of content are related prior to movement of a selected content by the user;

FIG. 4b is a detailed user interface diagram, showing the grid component of the user interface of FIG. 3 and illustrating how items of content move according to a user-designated trajectory and further illustrating how items of content are rearranged during such movement according to their respective degrees of relatedness;

FIG. 5 illustrates an alternate embodiment that features a control mechanism that permits a user to adjust a relatedness threshold or correlation metric threshold which regulates how many items of content are attracted during movement along the user-designated trajectory;

FIG. 6 is a software block diagram, illustrating the manner of programming the computer hardware of FIG. 2, it being understood that the depicted software is stored in the computer memory and operated upon by the CPU;

FIG. 7 is a flowchart diagram depicting one preferred embodiment whereby selected content is analyzed and motion of that content is generated by the suitably programmed computer hardware;

FIG. 8 is a graphical representation of one embodiment of a computer-implemented model for controlling how motion of content is generated by the suitably programmed computer hardware, the model featuring a display space reflecting how items of content are positioned and move within the display space of the computer screen;

FIG. 9 is a flow chart diagram explaining the operation of the information appliance according to the model of FIG. 8;

FIGS. 10a-10d illustrate the information appliance in use, performing a basic screen transition according to user operation;

FIGS. 11a-11d illustrate the information appliance in use, creating a personal category for an individual user or the user\'s family;

FIGS. 12a-12d illustrate the information appliance in use, creating a different category from the same content;

FIGS. 13a-13d illustrate the information appliance in use, creating a compound cluster from plural previously created clusters;

FIG. 14a is a detailed user interface diagram, showing an alternate embodiment of how items of content are related prior to movement of a selected content by the user according to a tree structure;

FIG. 14b is a detailed user interface diagram, illustrating how items of content of FIG. 14a move according to a user-designated trajectory and further illustrating how items of content are rearranged during such movement according to their respective degrees of relatedness and based on the tree structure;

FIG. 15 is a graphical representation of the alternate embodiment of FIGS. 14a and 14b, namely a computer-implemented model for controlling how motion of content is generated by the suitably programmed computer hardware, the model featuring a display space reflecting how items of content are positioned and move within the display space of the computer screen according to a tree structure; and

FIG. 16 illustrates a variation of the embodiment of FIGS. 14a and 14b that features a control mechanism that permits a user to adjust a relatedness threshold or correlation metric threshold which regulates how many items of content are attracted during movement along the user-designated trajectory.

Corresponding reference numerals indicate corresponding parts throughout the several views of the drawings.

DETAILED DESCRIPTION

Example embodiments will now be described more fully with reference to the accompanying drawings.

As noted above, the computer-implemented apparatus and method for organization, categorization and extraction of computerized content, defines a relationship between relatedness between targeted content and other content using a predefined physical parameter. The present description will explain in detail how to implement different examples of such apparatus and methods, using different examples of predefined physical parameters. By way of non-limiting example, the predefined physical parameter can be a kinematic-related parameter, such as be a force, a speed, a relative position, or the like.

In this regard, an exemplary physical parameter can be the force acting between related content (or icons) and targeted content (or icons), such as tensile force and attractive force. Such force is generated by computer according to the following relationships:

{right arrow over (F)}=ki({right arrow over (x)}i−{right arrow over (x)}T) {right arrow over (F)}: Force acting between related content/icon i and targeted content/icon T ki: Parameter depending on relatedness between related content/icon i and targeted content/icon T (ki>0) {right arrow over (x)}i: Position of related content/icon i {right arrow over (x)}T: Position of targeted content/icon T

Alternatively, the physical parameter can be a speed parameter, representing, for example, the speed with which related content (or icons) are attracted to the target content (or target icon). Such speed is generated by computer according to the following relationships:

x → i  ( t ) = x → i  ( t - Δ   t ) + x → i  ( t - Δ   t ) - x → T  ( t - Δ   t ) l i {right arrow over (x)}i(t): Position of related content/icon i at time t {right arrow over (x)}T(t): Position of targeted content/icon T at time t li: Parameter depending on relatedness between related content/icon i and targeted content/icon T (li>1)

Alternatively, the physical parameter can be a position parameter, representing, for example, the final position of related content (or icon) relative to the targeted content (or icon). Such relative position is generated by computer according to the following relationships:

Final relative position of related content/icon i, {right arrow over (r)}i={right arrow over (x)}i,FINAL−{right arrow over (x)}T,FINAL, is set depending on relatedness between related content/icon i and targeted content/icon T. For example, related contents are assigned at the final time in decreasing order of relatedness, most closely-related first, as below:

Here, in terms of speed with which related content/icon comes close to the position of {right arrow over (x)}T+{right arrow over (r)}i, it becomes like the following;

x → i  ( t ) = x → i  ( t - Δ   t ) + x →

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