Flickr group recommendation based on tensor decomposition

Nan Zheng, Qiudan Li, Shengcai Liao, Leiming Zhang

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

40 Citations (Scopus)

Abstract

Over the last few years, Flickr has gained massive popularity and groups in Flickr are one of the main ways for photo diffusion. However, the huge volume of groups brings troubles for users to decide which group to choose. In this paper, we propose a tensor decomposition-based group recommendation model to suggest groups to users which can help tackle this problem. The proposed model measures the latent associations between users and groups by considering both semantic tags and social relations. Experimental results show the usefulness of the proposed model.

Original languageEnglish
Title of host publicationSIGIR 2010 Proceedings - 33rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval
Pages737-738
Number of pages2
DOIs
Publication statusPublished - 2010
Externally publishedYes
Event33rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2010 - Geneva, Switzerland
Duration: Jul 19 2010Jul 23 2010

Publication series

NameSIGIR 2010 Proceedings - 33rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval

Conference

Conference33rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2010
Country/TerritorySwitzerland
CityGeneva
Period7/19/107/23/10

Keywords

  • Flickr group
  • Group recommendation
  • Tensor decomposition

ASJC Scopus subject areas

  • Information Systems

Fingerprint

Dive into the research topics of 'Flickr group recommendation based on tensor decomposition'. Together they form a unique fingerprint.

Cite this