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A CRITERION BASED ON FISHERS EXACT TEST FOR ITEM SPLITTING IN CONTEXT-AWARE RECOMMENDER SYSTEMS

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dc.creatorPEDRO GERÓNIMO CAMPOS SOTO
dc.date2016
dc.date.accessioned2025-01-10T14:29:25Z
dc.date.available2025-01-10T14:29:25Z
dc.date.issued2016
dc.description.abstractITEM SPLITTING IS A CONTEXT-AWARE RECOMMENDATION TECHNIQUE BASED ON COLLABORATIVE FILTERING (CF), WHICH GROUPS AND EXPLOITS RATINGS ACCORDING TO THE CONTEXTS IN WHICH THEY WERE GENERATED. IT SHOWS POSITIVE EFFECTS ON RECOMMENDATION ACCURACY IN THE PRESENCE OF SIGNIFICANT DIFFERENCES BETWEEN THE USERS' PREFERENCES FROM DISTINCT CONTEXTS. TO DETERMINE WHETHER SUCH DIFFERENCES ARE SIGNIFICANT, IN THIS PAPER WE PROPOSE A NOVEL IMPURITY CRITERION BASED ON THE FISHER'S EXACT TEST, WHICH RETURNS A SCORE ON THE DIFFERENCE BETWEEN RATINGS GIVEN TO AN ITEM. EXPERIMENTAL RESULTS ON A DATASET OF MOVIE RATINGS SHOW A LOWER RATING PREDICTION ERROR WITH RESPECT TO OTHER IMPURITY CRITERIA - IN PARTICULAR, RELATED WITH TIME CONTEXT SIGNALS - , LETTING US IMPROVE THE RECOMMENDATION PERFORMANCE OF A STATE-OF-THE-ART CF ALGORITHM IN AN OFFLINE EVALUATION SETTING THAT SIMULATES REAL-WORLD CONDITIONS.
dc.formatapplication/pdf
dc.identifier.doi10.1109/SCCC.2014.37
dc.identifier.issn1522-4902
dc.identifier.urihttps://repositorio.ubiobio.cl/handle/123456789/7659
dc.languagespa
dc.publisher33RD INTERNATIONAL CONFERENCE OF THE CHILEAN COMPUTER SCIENCE SOCIETY (SCCC)
dc.relation.uri10.1109/SCCC.2014.37
dc.rightsPUBLICADA
dc.titleA CRITERION BASED ON FISHERS EXACT TEST FOR ITEM SPLITTING IN CONTEXT-AWARE RECOMMENDER SYSTEMS
dc.title.alternativeUN CRITERIO BASADO EN LA PRUEBA EXACTA DE FISHER PARA LA DIVISIÓN DE ELEMENTOS EN SISTEMAS DE RECOMENDACIÓN CONSCIENTES DEL CONTEXTO
dc.typeACTA DE CONFERENCIA
dspace.entity.typePublication
ubb.EstadoPUBLICADA
ubb.Otra ReparticionDEPARTAMENTO DE SISTEMAS DE INFORMACION
ubb.SedeCONCEPCIÓN
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