iRIN: Image retrieval in image-rich information networks

Xin Jin, Jiebo Luo, Jie Yu, Gang Wang, Dhiraj Joshi, Jiawei Han

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

Abstract

In this demo, we present a system called iRIN designed for performing image retrieval in image-rich information networks. We first introduce MoK-SimRank to significantly improve the speed of SimRank, one of the most popular algorithms for computing node similarity in information networks. Next, we propose an algorithm called SimLearn to (1) extend MoK-SimRank to heterogeneous image-rich information network, and (2) account for both link-based and content-based similarities by seamlessly integrating reinforcement learning with feature learning.

Original languageEnglish (US)
Title of host publicationProceedings of the 19th International Conference on World Wide Web, WWW '10
Pages1261-1264
Number of pages4
DOIs
StatePublished - 2010
Event19th International World Wide Web Conference, WWW2010 - Raleigh, NC, United States
Duration: Apr 26 2010Apr 30 2010

Publication series

NameProceedings of the 19th International Conference on World Wide Web, WWW '10

Other

Other19th International World Wide Web Conference, WWW2010
CountryUnited States
CityRaleigh, NC
Period4/26/104/30/10

Keywords

  • image retrieval
  • information network
  • ranking

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications

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