Analysis and evaluation of recommendation systems

Emiko Orimo, Hideki Koike, Toshiyuki Masui, Akikazu Takeuchi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Popular online services, such as Amazon.com, provide recommendations for users by using other users' rating scores for items. In this study, we describe three types of rating systems: score-rated, count-rated, and digital-rated. We hypothesize that digital-rated systems provide the most useful recommendations. Then we analyze the differences in the results of the rating when the granularity of the score changes. Finally, we visualize users by developing a 2-D visualization system that uses a multi-dimensional scaling method.

Original languageEnglish
Title of host publicationHuman Interface and the Management of Information
Subtitle of host publicationMethods, Techniques and Tools in Information Design - Symposium on Human Interface 2007. Held as Part of HCI International 2007, Proceedings
PublisherSpringer Verlag
Pages144-152
Number of pages9
EditionPART 1
ISBN (Print)9783540733447
DOIs
Publication statusPublished - 2007
Externally publishedYes
EventSymposium on Human Interface 2007 - Beijing, China
Duration: 2007 Jul 222007 Jul 27

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume4557 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

OtherSymposium on Human Interface 2007
CountryChina
CityBeijing
Period07/7/2207/7/27

Keywords

  • Multi-dimensional scaling method
  • Rating algorithm
  • Recommendation system
  • Visualization

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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