On the fractal nature of mutual relevance sequences in the Internet news message flows

TL;DR

This paper explores the fractal properties of mutual relevance sequences in Internet news message flows, proposing a new approach to measure document relevance without restrictions, applicable to various relevance measures.

Contribution

It introduces a novel fractal analysis of relevance sequences and a flexible relevance measure approach for information retrieval systems.

Findings

Relevance sequences exhibit fractal characteristics.

The proposed relevance measure is adaptable to different retrieval scenarios.

Fractal analysis can improve understanding of information flow patterns.

Abstract

In the task of information retrieval the term relevance is taken to mean formal conformity of a document given by the retrieval system to user's information query. As a rule, the documents found by the retrieval system should be submitted to the user in a certain order. Therefore, a retrieval perceived as a selection of documents formally solving the user's query, should be supplemented with a certain procedure of processing a relevant set. It would be natural to introduce a quantitative measure of document conformity to query, i.e. the relevance measure. Since no single rule exists for the determination of the relevance measure, we shall consider two of them which are the simplest in our opinion. The proposed approach does not suppose any restrictions and can be applied to other relevance measures.