This work proposes the Bing-CSF-IDF+ recommender – a content-based recommender that makes use of semantic relationships, and combines the best features of our earlier introduced Bing-SF-IDF+ and CF-IDF+ systems. First, we make use of concepts and concept relationships from a domain ontology. Next, Bing-CSF-IDF+ employs the synsets and synset relationships from a semantic lexicon that have not been previously captured by the domain ontology. Last, named entities and their frequencies as provided by Bing – not present in the semantic lexicon and domain ontology – are utilized. Our experiments show that Bing-CSF-IDF+ significantly outperforms Bing-SF-IDF+ and CF-IDF+ on scores and Kappa statistics based on a news data set.,
Communications in Computer and Information Science
Erasmus University Rotterdam

van Huijsduijnen, L.H. (Lies Hooft), Hoogmoed, T. (Thom), Keulers, G. (Geertje), Langendoen, E. (Edmar), Langendoen, S. (Sanne), Vos, T. (Tim), … Robal, T. (Tarmo). (2020). Bing-CSF-IDF+: A Semantics-Driven Recommender System for News. In Communications in Computer and Information Science. doi:10.1007/978-3-030-54623-6_13