@book{
 title = {Modelling hierarchical relationships in group recommender systems},
 type = {book},
 year = {2015},
 source = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
 identifiers = {[object Object]},
 volume = {9343},
 id = {bada3e3c-e16f-3b95-954c-e125e288793e},
 created = {2017-12-11T12:30:38.185Z},
 file_attached = {false},
 profile_id = {93b02a20-88c2-31ac-b399-224e27b8cf85},
 last_modified = {2017-12-11T12:30:38.185Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {© Springer International Publishing Switzerland 2015. Group recommender systems have become systems of great interest in the CBR community. In previous papers we have described and validated a social recommendation model that solves different group recommendation challenges using knowledge from social networks. In this paper we have run across two identified limitations of our model, unprofiled users and “hierarchical relations” within a group, and have proposed and validated CBR solutions for them.},
 bibtype = {book},
 author = {Quijano-Sánchez, L. and Recio-García, J.A. and Díaz-Agudo, B.}
}

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