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 publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages144-152
Number of pages9
Volume4557 LNCS
EditionPART 1
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)03029743
ISSN (Electronic)16113349

Other

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

Fingerprint

Recommendation System
Recommender systems
Visualization
Recommendations
Evaluation
Granularity
Count
Scaling

Keywords

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

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

Cite this

Orimo, E., Koike, H., Masui, T., & Takeuchi, A. (2007). Analysis and evaluation of recommendation systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (PART 1 ed., Vol. 4557 LNCS, pp. 144-152). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4557 LNCS, No. PART 1).

Analysis and evaluation of recommendation systems. / Orimo, Emiko; Koike, Hideki; Masui, Toshiyuki; Takeuchi, Akikazu.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4557 LNCS PART 1. ed. 2007. p. 144-152 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4557 LNCS, No. PART 1).

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

Orimo, E, Koike, H, Masui, T & Takeuchi, A 2007, Analysis and evaluation of recommendation systems. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). PART 1 edn, vol. 4557 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 4557 LNCS, pp. 144-152, Symposium on Human Interface 2007, Beijing, China, 07/7/22.
Orimo E, Koike H, Masui T, Takeuchi A. Analysis and evaluation of recommendation systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). PART 1 ed. Vol. 4557 LNCS. 2007. p. 144-152. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).
Orimo, Emiko ; Koike, Hideki ; Masui, Toshiyuki ; Takeuchi, Akikazu. / Analysis and evaluation of recommendation systems. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4557 LNCS PART 1. ed. 2007. pp. 144-152 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).
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