On Affinity Measures for Artificial Immune System Movie Recommenders

dc.creatorAickelin, Uwe
dc.creatorChen, Qi
dc.date2008-01-28
dc.date2008-05-16
dc.date.accessioned2026-07-07T09:38:57Z
dc.date.available2026-07-07T09:38:57Z
dc.descriptionWe combine Artificial Immune Systems 'AIS', technology with Collaborative Filtering 'CF' and use it to build a movie recommendation system. We already know that Artificial Immune Systems work well as movie recommenders from previous work by Cayzer and Aickelin 3, 4, 5. Here our aim is to investigate the effect of different affinity measure algorithms for the AIS. Two different affinity measures, Kendalls Tau and Weighted Kappa, are used to calculate the correlation coefficients for the movie recommender. We compare the results with those published previously and show that Weighted Kappa is more suitable than others for movie problems. We also show that AIS are generally robust movie recommenders and that, as long as a suitable affinity measure is chosen, results are good.
dc.identifierhttps://arxiv.org/abs/0801.4307
dc.identifierhttp://arxiv.org/abs/0801.4307
dc.identifierProceedings of the 5th International Conference on Recent Advances in Soft Computing (RASC 2004), Nottingham, UK
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/160997
dc.subjectNeural and Evolutionary Computing
dc.subjectArtificial Intelligence
dc.subjectComputers and Society
dc.titleOn Affinity Measures for Artificial Immune System Movie Recommenders
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