Investigating contextual ontologies and document corpus characteristics for information access in engineering settings

Abstract

Knowledge and information are valuable resources in enterprises for solution reuse. However, identifying relevant information from a rapidly growing number of unstructured resources is challenging for users. We discuss a personalized information access tool for professional workplaces based on recommender systems to provide relevant documents for users in specific work contexts based on domain-specific ontologies. Our use case is a multidisciplinary engineering project. We provide an in-depth analysis on the content and context of documents using information retrieval methods and semantic annotations. Upon this, we build a contextual ontology as our knowledge domain for the recommender system and evaluate the level of retrievability and coverage of it against the documents. Our results provide insight into engineers’ document workspaces and show that even a simple domain ontology is able to match a majority of documents from a domain-oriented corpus. The findings support our approach of using ontology-based recommendation for domain-specific workspaces.