Visualizing Recommendation Flow on Social Network

dc.creatorJung,Jason
dc.date2005
dc.date.accessioned2024-02-06T12:53:54Z
dc.date.available2024-02-06T12:53:54Z
dc.descriptionIn contrast with centralized recommender systems, social recommendation algorithm is applied to the item rating data on social networks. Meaningful recommendation can be uncovered by the topology of social network as well as the similarity between users. More importantly, this information becomes propagated into the users in the estimated same groups. As the goal of this paper, we propose a novel method for visual explanation of the recommender system on social network. For experiments, we simulate the recommendation flow by using the MovieLens dataset on a social network constructed with FOAF.
dc.formattext/html
dc.identifierhttps://doi.org/10.3217/jucs-011-11-1780
dc.identifierhttps://lib.jucs.org/article/28502/
dc.identifier.urihttps://openrepository.mephi.ru/handle/123456789/8876
dc.languageen
dc.publisherJournal of Universal Computer Science
dc.relationinfo:eu-repo/semantics/altIdentifier/eissn/0948-6968
dc.relationinfo:eu-repo/semantics/altIdentifier/pissn/0948-695X
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightsJ.UCS License
dc.sourceJUCS - Journal of Universal Computer Science 11(11): 1780-1791
dc.subjectreputation
dc.subjectsocial network
dc.subjectvisualizing information flow
dc.titleVisualizing Recommendation Flow on Social Network
dc.typeResearch Article
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