Mining and Composition of Emergent Collectives in Mixed Service-Oriented Systems

Abstract

Complex service-oriented systems typically span interactions between people and services. Compositions in such systems demand for flexible interaction models. In this work we introduce an approach for discovering experts based on their dynamically changing skills and interests. We discuss human provided services and an approach for managing user preferences and network structures. Experts offer their skills and capabilities as human provided services that can be requested on demand. Our main contributions center around an expert discovery method based on the concept of hubs and authorities in Web-based environments. The presented discovery and interaction approach takes trust-relations and link properties in social networks into account to estimate the hub-expertise of users. Furthermore, we show how our approach supports flexible interactions in mixed service-oriented systems.