?url_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rft.title=Slope+One+Predictors+for+Online+Rating-Based+Collaborative+Filtering&rft.creator=Lemire%2C+Daniel&rft.creator=Maclachlan%2C+Anna&rft.subject=Machine+Learning&rft.description=Rating-based+collaborative+filtering+is+the+process+of+predicting+how+a+user+would+rate+a+given+item+from+other+user+ratings.+We+propose+three+related+slope+one+schemes+with+predictors+of+the+form+f(x)+%3D+x+%2B+b%2C+which+precompute+the+average+difference+between+the+ratings+of+one+item+and+another+for+users+who+rated+both.+Slope+one+algorithms+are+easy+to+implement%2C+efficient+to+query%2C+reasonably+accurate%2C+and+they+support+both+online+queries+and+dynamic+updates%2C+which+makes+them+good+candidates+for+real-world+systems.+The+basic+slope+one+scheme+is+suggested+as+a+new+reference+scheme+for+collaborative+filtering.+By+factoring+in+items+that+a+user+liked+separately+from+items+that+a+user+disliked%2C+we+achieve+results+competitive+with+slower+memory-based+schemes+over+the+standard+benchmark+EachMovie+and+Movielens+data+sets+while+better+fulfilling+the+desiderata+of+CF+applications.&rft.publisher=SIAM&rft.date=2005&rft.type=Conference+Paper&rft.type=PeerReviewed&rft.format=application%2Fpdf&rft.identifier=http%3A%2F%2Fcogprints.org%2F4031%2F1%2Flemiremaclachlan_sdm05.pdf&rft.identifier=++Lemire%2C+Daniel+and+Maclachlan%2C+Anna++(2005)+Slope+One+Predictors+for+Online+Rating-Based+Collaborative+Filtering.++%5BConference+Paper%5D+++++&rft.relation=http%3A%2F%2Fcogprints.org%2F4031%2F