The ever-increasing amount of Web information offered to news readers (e.g., news analysts) stimulates the need for news selection, so that informed decisions can be made with up-to-date knowledge. Hermes is an ontology-based framework for building news personalization services. It uses an ontology crafted from available news sources, allowing users to select and filter interesting concepts from a domain ontology. The Aethalides framework enhances the Hermes framework by enabling news classification through lexicographic and semantic properties. For this, Aethalides applies word sense disambiguation and ontology learning methods to news items. When tested on a set of news items on finance and politics, the Aethalides implementation yields a precision and recall of 74.4% and 49.4%, respectively, yielding an F0.5-measure of 67.6% when valuing precision more than recall.

News personalization, Ontology learning, Semantic web, Word sense disambiguation,
Journal of Web Engineering
Department of Econometrics

Rijvordt, W, Hogenboom, F.P, & Frasincar, F. (2019). Ontology-driven news classification with aethalides. Journal of Web Engineering, 18(7), 627–654. doi:10.13052/jwe1540-9589.1873