Stochastic Self-Organisation of Poorly Structured Data and Memory Realisation in an Information Domain When Designing News Events Forecasting Models

摘要

The paper expands on the elaborated model of forecasting news events basing on the stochastic dynamics of news clusters variance and memory-based realisation in an information domain with self-organizing poorly structured data. The provided analysis of stochastic dynamics in overcoming the news events threshold shows the transition probability appearing right after the process of changing the news clusters dimensions and structure begins. The allowances for the second time derivative in the differential model of information process enable accounting for the memory of the previous states of the information system and the possibility to describe the system's considerable self-organisation. Basing on the developed model, the authors have designed an algorithm of analysing the interrelations of news clusters in the information domain with a probability for a forecast event happening, and defining a possible time of its occurrence.