Cross-domain mediation in collaborative filtering

Shlomo Berkovsky, Tsvi Kuflik, Francesco Ricci

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


One of the main problems of collaborative filtering recommenders is the sparsity of the ratings in the users-items matrix, and its negative effect on the prediction accuracy. This paper addresses this issue applying cross-domain mediation of collaborative user models, i.e., importing and aggregating vectors of users' ratings stored by collaborative systems operating in different application domains. The paper presents several mediation approaches and initial experimental evaluation demonstrating that the mediation can improve the accuracy of the generated predictions.

Original languageEnglish
Title of host publicationUser Modeling 2007 - 11th International Conference, UM 2007, Proceedings
PublisherSpringer Verlag
Number of pages5
ISBN (Print)9783540730774
StatePublished - 2007
Event11th International on User Modeling Conference, UM 2007 - Corfu, Greece
Duration: 25 Jun 200729 Jun 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4511 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference11th International on User Modeling Conference, UM 2007

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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