Faceted exploration of image search results

  • Authors:
  • Roelof van Zwol;Börkur Sigurbjornsson;Ramu Adapala;Lluis Garcia Pueyo;Abhinav Katiyar;Kaushal Kurapati;Mridul Muralidharan;Sudar Muthu;Vanessa Murdock;Polly Ng;Anand Ramani;Anuj Sahai;Sriram Thiru Sathish;Hari Vasudev;Upendra Vuyyuru

  • Affiliations:
  • Yahoo!, Barcelona, Spain;Yahoo!, Barcelona, Spain;Yahoo!, Bangalore, India;Yahoo!, Barcelona, Spain;Yahoo!, Bangalore, Spain;Yahoo!, Sunnyvale, USA;Yahoo!, Bangalore, India;Yahoo!, Bangalore, India;Yahoo!, Barcelona, Spain;Yahoo!, New York, USA;Yahoo!, Bangalore, India;Yahoo!, Bangalore, India;Yahoo!, Bangalore, India;Yahoo!, Barcelona, India;Yahoo!, Bangalore, India

  • Venue:
  • Proceedings of the 19th international conference on World wide web
  • Year:
  • 2010

Quantified Score

Hi-index 0.00

Visualization

Abstract

This paper describes MediaFaces, a system that enables faceted exploration of media collections. The system processes semi-structured information sources to extract objects and facets, e.g. the relationships between two objects. Next, we rank the facets based on a statistical analysis of image search query logs, and the tagging behaviour of users annotating photos in Flickr. For a given object of interest, we can then retrieve the top-k most relevant facets and present them to the user. The system is currently deployed in production by Yahoo!'s image search engine1. We present the system architecture, its main components, and the application of the system as part of the image search experience.