Observatorio de I+D+i UPM

Memorias de investigación
Research Publications in journals:
A collaborative filtering similarity measure based on singularities
Year:2012
Research Areas
  • Computer system,
  • Dataprocessing
Information
Abstract
Recommender systems play an important role in reducing the negative impact of informa- tion overload on those websites where users have the possibility of voting for their prefer- ences on items. The most normal technique for dealing with the recommendation mechanism is to use collaborative filtering, in which it is essential to discover the most similar users to whom you desire to make recommendations. The hypothesis of this paper is that the results obtained by applying traditional similarities measures can be improved by taking contextual information, drawn from the entire body of users, and using it to cal- culate the singularity which exists, for each item, in the votes cast by each pair of users that you wish to compare. As such, the greater the measure of singularity result between the votes cast by two given users, the greater the impact this will have on the similarity. The results, tested on the Movielens, Netflix and FilmAffinity databases, corroborate the excellent behaviour of the singularity measure proposed.
International
Si
JCR
Si
Title
Information Processing & Management
ISBN
0306-4573
Impact factor JCR
1,673
Impact info
Datos JCR del año 2010
Volume
48
Journal number
2
From page
204
To page
217
Month
SIN MES
Ranking
Participants
  • Autor: Fernando Ortega Requena (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: MERCATOR Tecnologías de la GeoInformación
  • Departamento: Lenguajes, Proyectos y Sistemas Informáticos
S2i 2020 Observatorio de investigación @ UPM con la colaboración del Consejo Social UPM
Cofinanciación del MINECO en el marco del Programa INNCIDE 2011 (OTR-2011-0236)
Cofinanciación del MINECO en el marco del Programa INNPACTO (IPT-020000-2010-22)