Using linked data to classify web documents

Abstract

Purpose: The purpose of this paper is to find a relationship between traditional faceted classification schemes and semantic web document annotators, particularly in the linked data environment. Design/methodology/approach: A consideration of the conceptual ideas behind faceted classification and linked data architecture is made. Analysis of selected web documents is performed using Calais' Semantic Proxy to support the considerations. Findings: Technical language aside, the principles of both approaches are very similar. Modern classification techniques have the potential to automatically generate metadata to drive more precise information recall by including a semantic layer. Originality/value: Linked data have not been explicitly considered in this context before in the published literature. © Emerald Group Publishing Limited.