Explanation of Recommenders Using Formal Concept Analysis. Diaz-Agudo, B., Caro-Martinez, M., Recio-Garcia, J., Jorro-Aragoneses, J., & Jimenez-Diaz, G. Volume 11680 LNAI , 2019.
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© 2019, Springer Nature Switzerland AG. Formal Concept Analysis is a mathematical approach which enables formalisation of concepts as basic units of human thinking and analysing data in the object-attribute form. In this paper, we propose the use of FCA as a general resource for explanations and apply it to explain the results of recommender systems. Our method is reusable and applicable to different domains. We define different types of explanations by travelling the lattice structure and analyse how the lattice metrics can be used to characterise the different types of user profiles.
@book{
 title = {Explanation of Recommenders Using Formal Concept Analysis},
 type = {book},
 year = {2019},
 source = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
 keywords = {Explainable artificial intelligence,Explanations,Formal concept analysis,Recommender systems},
 volume = {11680 LNAI},
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 created = {2019-10-11T23:59:00.000Z},
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 abstract = {© 2019, Springer Nature Switzerland AG. Formal Concept Analysis is a mathematical approach which enables formalisation of concepts as basic units of human thinking and analysing data in the object-attribute form. In this paper, we propose the use of FCA as a general resource for explanations and apply it to explain the results of recommender systems. Our method is reusable and applicable to different domains. We define different types of explanations by travelling the lattice structure and analyse how the lattice metrics can be used to characterise the different types of user profiles.},
 bibtype = {book},
 author = {Diaz-Agudo, B. and Caro-Martinez, M. and Recio-Garcia, J.A. and Jorro-Aragoneses, J. and Jimenez-Diaz, G.},
 doi = {10.1007/978-3-030-29249-2_3}
}

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