The Structural Information Potential and its Application to Document Triage

Abstract

This article introduces structural information potential (SIP), a measure of information based on the potential of structures to be informative about their content. An example of this concept is the clustered appearance that typically characterizes the first page of scientific articles, which summarizes the article’s contents and provides additional data, yielding potentially the largest and most diverse amount of information from a single page in the shortest time with the least effort. This characteristic makes SIP particularly well-adapted to triage tasks (i.e., rapid decision-making under conditions of uncertainty and limited resources), an application illustrated by means of a case study on classifying document images. The SIP method consists in unifying the Shannon entropy, the Fourier transform, the fractal dimension, and the golden ratio into a single equation and several algorithmic components. While the application domain is document images, the concept has generic character. The method results in a mathematically and perceptually coherent pattern space, characterized by continuous transition between uniform, clustered, and regular configurations, and corresponding to a structural information potential with a well-defined maximum. The maximum SIP leads to the identification of shapes and patterns with minimal structural redundancy, termed “fluorescent objects” as a complement to regular graphs and the Platonic solids.