Filtering information in a connected network

TL;DR

This paper proposes a novel information filtering method based on a new Information Theory, aiming to robustly identify high-ranking information from noisy local comparisons, with promising analytical and numerical results.

Contribution

It introduces a new kind of Information Theory and a filtering model that operates on noisy local comparisons, with potential applications in future Internet information selection.

Findings

Encouraging analytical results

Promising numerical results

Potential wide-ranging implications

Abstract

We introduce a new kind of Information Theory. From a finite number of local, noisy comparisons, we want to design a robust filter such that the outcome is a high ranking number, Both analytical and numerical results are encouraging and we believe our toy model has wide ranging implications in the future Internet-based information selection mechanism.