Expert-Finding Systems for Organizations: Problem and Domain Analysis and the DEMOIR Approach

TLDR

Computer systems that facilitate expert discovery within organizations or globally are increasingly feasible due to widespread corporate intranets and the Internet. This article investigates expert‑finding systems in two parts: first, exploring the problem and reviewing existing solutions, and second, identifying gaps that remain to be addressed. The authors analyze the expert‑finding problem, review current systems, propose a domain model, and present DEMOIR, a modular architecture that combines a centralized expertise‑modeling server with decentralized components for gathering and exploiting expertise information. The investigation uncovers gaps in current expert‑finding systems that warrant further development.

Abstract

Abstract Computer systems that augment the process of finding, in an organization or worldwide, the appropriate expert for a given problem are becoming more feasible than ever as a result of the prevalence of corporate intranets and the Internet. In this article, we investigate such systems in 2 parts. First, we explore the expert-finding problem in depth, review and analyze existing systems in this domain, and suggest a domain model that can serve as a framework for design and development decisions. Second, on the basis of our analyses of the problem and solution spaces, we bring to light the gaps that remain to be addressed. Finally, after this two-part investigation, we present our approach, called DEMOIR (dynamic expertise modeling from organizational information resources), which is a modular architecture for expert-finding systems that is based on a centralized expertise-modeling server but also incorporates decentralized components for expertise information gathering and exploitation.