Semantic Social Recommendations in Knowledge-Based Engineering

We examine the application of semantic context-aware Recommender Systems to improve interaction and navigation in a design-centric engineering domain. The small scale of this specialised environment renders most Web-scale solutions unsuitable, mandating tailored approaches. We report on initial work to identify challenges and promising categories of personalisation and adaptation together with relevant context features taken from the whole environment consisting of users, organisation, and documents to overcome the sparsity issue in professional Information Access.