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An Enhanced Semantic Layer for Hybrid Recommender Systems: Application to News Recommendation

An Enhanced Semantic Layer for Hybrid Recommender Systems: Application to News Recommendation

Iván Cantador, Pablo Castells, Alejandro Bellogín
Copyright: © 2013 |Pages: 35
ISBN13: 9781466636101|ISBN10: 1466636106|EISBN13: 9781466636118
DOI: 10.4018/978-1-4666-3610-1.ch010
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MLA

Cantador, Iván, et al. "An Enhanced Semantic Layer for Hybrid Recommender Systems: Application to News Recommendation." Semantic Web: Ontology and Knowledge Base Enabled Tools, Services, and Applications, edited by Amit Sheth, IGI Global, 2013, pp. 235-269. https://doi.org/10.4018/978-1-4666-3610-1.ch010

APA

Cantador, I., Castells, P., & Bellogín, A. (2013). An Enhanced Semantic Layer for Hybrid Recommender Systems: Application to News Recommendation. In A. Sheth (Ed.), Semantic Web: Ontology and Knowledge Base Enabled Tools, Services, and Applications (pp. 235-269). IGI Global. https://doi.org/10.4018/978-1-4666-3610-1.ch010

Chicago

Cantador, Iván, Pablo Castells, and Alejandro Bellogín. "An Enhanced Semantic Layer for Hybrid Recommender Systems: Application to News Recommendation." In Semantic Web: Ontology and Knowledge Base Enabled Tools, Services, and Applications, edited by Amit Sheth, 235-269. Hershey, PA: IGI Global, 2013. https://doi.org/10.4018/978-1-4666-3610-1.ch010

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Abstract

Recommender systems have achieved success in a variety of domains, as a means to help users in information overload scenarios by proactively finding items or services on their behalf, taking into account or predicting their tastes, priorities, or goals. Challenging issues in their research agenda include the sparsity of user preference data and the lack of flexibility to incorporate contextual factors in the recommendation methods. To a significant extent, these issues can be related to a limited description and exploitation of the semantics underlying both user and item representations. The authors propose a three-fold knowledge representation, in which an explicit, semantic-rich domain knowledge space is incorporated between user and item spaces. The enhanced semantics support the development of contextualisation capabilities and enable performance improvements in recommendation methods. As a proof of concept and evaluation testbed, the approach is evaluated through its implementation in a news recommender system, in which it is tested with real users. In such scenario, semantic knowledge bases and item annotations are automatically produced from public sources.

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