Abstract
In a recommendation task it is crucial to have an accurate content-based description of the users and the items. Linked Open Data (LOD) has been demonstrated as one of the best ways of obtaining this kind of content. The main question is to know how useful the LOD information is in inferring user preferences and how to obtain it. We propose a novel approach for Content Modelling and Recommendation based on Formal Concept Analysis (FCA). The approach is based in the modelling of the user and content related information, enriched with LOD, and in a new algorithm to analyze the models and recommend new content. The framework provided by the ESWC 2014 Recommendation Challenge is used for the evaluation. The results are within the average range of other participants, but further work has to be carried out to refine the approach using LOD information.
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Castellanos, A., García-Serrano, A., Cigarrán, J. (2014). Linked Data-based Conceptual Modelling for Recommendation: A FCA-Based Approach. In: Hepp, M., Hoffner, Y. (eds) E-Commerce and Web Technologies. EC-Web 2014. Lecture Notes in Business Information Processing, vol 188. Springer, Cham. https://doi.org/10.1007/978-3-319-10491-1_8
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DOI: https://doi.org/10.1007/978-3-319-10491-1_8
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