Abstract
We show how Formal Concept Analysis (FCA) can be applied to Collaborative Recommenders. FCA is a mathematical method for analysing binary relations. Here we apply it to the relation between users and items in a collaborative recommender system. FCA groups the users and items into concepts, ordered by a concept lattice. We present two new algorithms for finding neighbours in a collaborative recommender. Both use the concept lattice as an index to the recommender’s ratings matrix. Our experimental results show a major decrease in the amount of work needed to find neighbours, while guaranteeing no loss of accuracy or coverage.
This work is supported by the Boole Centre for Research in Informatics, University College Cork under the HEA-PRTLI scheme.
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© 2006 Springer-Verlag London Limited
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du Boucher-Ryan, P., Bridge, D. (2006). Collaborative Recommending using Formal Concept Analysis. In: Bramer, M., Coenen, F., Allen, T. (eds) Research and Development in Intelligent Systems XXII. SGAI 2005. Springer, London. https://doi.org/10.1007/978-1-84628-226-3_16
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DOI: https://doi.org/10.1007/978-1-84628-226-3_16
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