Ontology-based news recommendation

Autor: IJntema, W, Goossen, F, Frasincar, Flavius, Hogenboom, Frederik, Daniel, F., Truta, T.M., Volz, B., Waller, E., Xiong, L., Zimányi, E., Delcambre, L.M.L., Fotouhi, F., Garrigós, I., Guerrini, G., Mazón, J.-N., Mesiti, M., Müller-Feuerstein, S., Trujillo, J.
Přispěvatelé: Econometrics, Erasmus School of Economics
Rok vydání: 2010
Předmět:
Zdroj: EDBT/ICDT Workshops
International Workshop on Business intelligencE and the WEB (BEWEB 2010) at Thirteenth International Conference on Extending Database Technology and Thirteenth International Conference on Database Theory (EDBT/ICDT 2010), 426
DOI: 10.1145/1754239.1754257
Popis: Recommending news items is traditionally done by term-based algorithms like TF-IDF. This paper concentrates on the benefits of recommending news items using a domain ontology instead of using a term-based approach. For this purpose, we propose Athena, which is an extension to the existing Hermes framework. Athena employs a user profile to store terms or concepts found in news items browsed by the user. Based on this information, the framework uses a traditional method based on TF-IDF, and several ontology-based methods to recommend new articles to the user. The paper concludes with the evaluation of the different methods, which shows that the new ontology-based method that we propose in this paper performs better (w.r.t. accuracy, precision, and recall) than the traditional method and, with the exception of one measure (recall), also better than the other considered ontology-based approaches.
Databáze: OpenAIRE