An Uncertainty Management Calculus for Ordering Searches in Distributed Dynamic Databases

TL;DR

This paper introduces a calculus for managing uncertainty in distributed search systems, enhancing adaptability by considering temporal, reliability, and saturation factors to improve document retrieval performance.

Contribution

It presents a novel uncertainty management calculus that incorporates temporal precedence, evidence reliability, and saturation effects for distributed search optimization.

Findings

The calculus effectively adapts to changing document distributions.

It improves search control by modeling certainty factors.

Initial results demonstrate enhanced system responsiveness.

Abstract

MINDS is a distributed system of cooperating query engines that customize, document retrieval for each user in a dynamic environment. It improves its performance and adapts to changing patterns of document distribution by observing system-user interactions and modifying the appropriate certainty factors, which act as search control parameters. It argued here that the uncertainty management calculus must account for temporal precedence, reliability of evidence, degree of support for a proposition, and saturation effects. The calculus presented here possesses these features. Some results obtained with this scheme are discussed.