Ways of computing diverse collaborative recommendations

  • Derek Bridge
  • , John Paul Kelly

Research output: Chapter in Book/Report/Conference proceedingsConference proceedingpeer-review

Abstract

Conversational recommander systems adapt the sets of products they recommend in light of user feedback. Our contribution here is to devise and compare four different mechanisms for enhancing the diversity of the recommendations made by collaborative recommenders. Significantly, we increase diversity using collaborative data only. We find that measuring the distance between products using Hamming Distance is more effective than using Inverse Pearson Correlation.

Original languageEnglish
Title of host publicationAdaptive Hypermedia and Adaptive Web-Based Systems - 4th International Conference, AH 2006
PublisherSpringer Verlag
Pages41-50
Number of pages10
ISBN (Print)3540346961, 9783540346968
DOIs
Publication statusPublished - 2006
Event4th International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems, AH 2006 - Dublin, Ireland
Duration: 21 Jun 200623 Jun 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4018 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference4th International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems, AH 2006
Country/TerritoryIreland
CityDublin
Period21/06/0623/06/06

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