Personal Recommendation via Modified Collaborative Filtering

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dc.creatorLiu, Runran
dc.creatorJia, Chunxiao
dc.creatorZhou, Tao
dc.creatorSun, Duo
dc.creatorWang, Binghong
dc.date2008-01-08
dc.date2008-07-27
dc.date.accessioned2026-07-07T12:11:47Z
dc.date.available2026-07-07T12:11:47Z
dc.descriptionIn this paper, we propose a novel method to compute the similarity between congeneric nodes in bipartite networks. Different from the standard Person correlation, we take into account the influence of node's degree. Substituting this new definition of similarity for the standard Person correlation, we propose a modified collaborative filtering (MCF). Based on a benchmark database, we demonstrate the great improvement of algorithmic accuracy for both user-based MCF and object-based MCF.
dc.description7 pages, 8 figures and 1 table
dc.identifierhttps://arxiv.org/abs/0801.1333
dc.identifierhttp://arxiv.org/abs/0801.1333
dc.identifierPhysica A 388 (2009) 462-468
dc.identifierdoi:10.1016/j.physa.2008.10.010
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/210333
dc.subjectData Analysis, Statistics and Probability
dc.subjectPhysics and Society
dc.titlePersonal Recommendation via Modified Collaborative Filtering
dc.typetext

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