Decoding the Text Encoding

TL;DR

This paper introduces an automatic algorithm to decode word cloud images, extracting underlying data with high accuracy, enabling better statistical analysis and visualization improvements.

Contribution

It is the first method to decode word clouds into raw data, enhancing visualization and analysis capabilities.

Findings

Effective extraction of words and weights from word clouds

Low error rate in data decoding

Validated through qualitative and quantitative tests

Abstract

Word clouds and text visualization is one of the recent most popular and widely used types of visualizations. Despite the attractiveness and simplicity of producing word clouds, they do not provide a thorough visualization for the distribution of the underlying data. Therefore, it is important to redesign word clouds for improving their design choices and to be able to do further statistical analysis on data. In this paper we have proposed a fully automatic redesigning algorithm for word cloud visualization. Our proposed method is able to decode an input word cloud visualization and provides the raw data in the form of a list of (word, value) pairs. To the best of our knowledge our work is the first attempt to extract raw data from word cloud visualization. We have tested our proposed method both qualitatively and quantitatively. The results of our experiments show that our algorithm is able to extract the words and their weights effectively with considerable low error rate.