Word Cloud Generation Inside Arbitrary Polygons
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Solution Overview
Problem
Generating a word cloud inside a predetermined polygon of arbitrary shape and size is computationally intensive, especially when determining the maximum word size that fills the shape without crossing its boundaries, and traditional word clouds only convey relative importance through size, lacking representation of multiple dimensions of information.
Innovation Solution
A method for quickly generating a word cloud by selecting a maximum word size using iterative algorithms that ensure words fit within the polygon, and representing each word with multiple scores for size and color based on psychometric descriptors, allowing for multi-dimensional visualization of textual and personality-related information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If traditional algorithms are used to arrange words inside a predefined polygon, then words can be displayed within the shape, but the computational complexity becomes intensive when searching for maximum word size
Solution Approach 1:
The patent transforms the continuous problem of finding maximum word size into a discrete search problem by parameterizing word sizes and using binary search to efficiently converge on the optimal size. This changes the approach from continuous optimization to discrete parameter searching, reducing computational complexity.
Solution Approach 2:
The patent performs preliminary actions by first calculating bounding boxes for all words, pre-processing the word list, and establishing the search space boundaries before beginning the actual word placement. This preliminary preparation reduces the complexity of the main placement algorithm.
2Loss of information
If traditional word clouds only use relative size to convey importance, then the visualization is simple, but multiple dimensions of information cannot be represented
Solution Approach 1:
The patent adds a new dimension to word cloud visualization by introducing color as an additional visual attribute alongside size. Each word is now represented by two dimensions: size (conveying importance/frequency) and color (conveying sentiment or category), allowing multiple dimensions of information to be encoded simultaneously without overwhelming the viewer.
Solution Approach 2:
The patent systematically uses color changes to encode additional information about words. By mapping sentiment scores or categories to color hues, the visualization can convey emotional tone or classification data alongside the traditional importance indication, enriching the information density of the word cloud.
Data Source
AI summary
A word cloud can quickly convey relative importance of words by displaying relatively important words larger than relatively unimportant words. Examples of the disclosure are directed to methods of generating a word cloud inside a predetermined polygon of arbitrary shape and size. For example, a word cloud may be generated with words to describe a particular company, and the word cloud may be generated inside the predefined shape of that company's logo, creating a single visualization that both describes and identifies the company. Further, whereas a traditional word cloud may illustrate relative word importance through relative word size, based on relative frequency of each word in a description or corpus, examples of the disclosure are directed to word clouds that can represent multiple dimensions of information for each word using size and color, for example.