Exploiting different users' interactions for profiles enrichment in recommender systems

dc.creatorCosta, Arthur Fortes da
dc.creatorMartins, Rafael D.
dc.creatorManzato, Marcelo Garcia
dc.creatorCampello, Ricardo José Gabrielli Barreto
dc.date.accessioned2016-10-19T21:41:10Z
dc.date.accessioned2018-07-04T17:10:46Z
dc.date.available2016-10-19T21:41:10Z
dc.date.available2018-07-04T17:10:46Z
dc.date.created2016-10-19T21:41:10Z
dc.date.issued2016-04
dc.identifierSymposium on Applied Computing, 31st, 2016, Pisa.
dc.identifier9781450337397
dc.identifierhttp://www.producao.usp.br/handle/BDPI/51001
dc.identifierhttp://dx.doi.org/10.1145/2851613.2851923
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1645728
dc.description.abstractUser profiling is an important aspect of recommender systems. It models users' preferences and is used to assess an item's relevance to a particular user. In this paper we propose a profiling approach which describes and enriches the users' preferences using multiple types of interactions. We show in our experiments that the enriched version of users' profiles is able to provide better recommendations.
dc.languageeng
dc.publisherAssociation for Computing Machinery - ACM
dc.publisherUniversity of Pisa
dc.publisherScuola Superiore Sant’Anna
dc.publisherPisa
dc.relationSymposium on Applied Computing, 31st
dc.rightsCopyright ACM
dc.rightsclosedAccess
dc.subjectRecommender system
dc.subjectuser profiling
dc.subjectmultiple interactions
dc.titleExploiting different users' interactions for profiles enrichment in recommender systems
dc.typeActas de congresos


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