Exploring an opinion network for taste prediction: An empirical study

Marcel Blattner, Yi Cheng Zhang, Sergei Maslov

Research output: Contribution to journalArticlepeer-review

Abstract

We develop a simple statistical method to find affinity relations in a large opinion network which is represented by a very sparse matrix. These relations allow us to predict missing matrix elements. We test our method on the Eachmovie data of thousands of movies and viewers. We found that significant prediction precision can be achieved and it is rather stable. There is an intrinsic limit to further improve the prediction precision by collecting more data, implying perfect prediction can never obtain via statistical means.

Original languageEnglish (US)
Pages (from-to)753-758
Number of pages6
JournalPhysica A: Statistical Mechanics and its Applications
Volume373
DOIs
StatePublished - Jan 1 2007
Externally publishedYes

Keywords

  • Opinion network
  • Recommender systems
  • Taste prediction

ASJC Scopus subject areas

  • Statistics and Probability
  • Condensed Matter Physics

Fingerprint Dive into the research topics of 'Exploring an opinion network for taste prediction: An empirical study'. Together they form a unique fingerprint.

Cite this