Table of Contents Author Guidelines Submit a Manuscript
Advances in Multimedia
Volume 2011, Article ID 310762, 18 pages
Research Article

Utilizing Implicit User Feedback to Improve Interactive Video Retrieval

1Centre for Research and Technology Hellas, Informatics and Telematics Institute, 6th Klm Charilaou-Thermi Road, 57001 Thessaloniki, Greece
2Queen Mary, University of London, Mile End Road, London E1 4NS, UK

Received 1 September 2010; Accepted 3 January 2011

Academic Editor: Andrea Prati

Copyright © 2011 Stefanos Vrochidis et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper describes an approach to exploit the implicit user feedback gathered during interactive video retrieval tasks. We propose a framework, where the video is first indexed according to temporal, textual, and visual features and then implicit user feedback analysis is realized using a graph-based methodology. The generated graph encodes the semantic relations between video segments based on past user interaction and is subsequently used to generate recommendations. Moreover, we combine the visual features and implicit feedback information by training a support vector machine classifier with examples generated from the aforementioned graph in order to optimize the query by visual example search. The proposed framework is evaluated by conducting real-user experiments. The results demonstrate that significant improvement in terms of precision and recall is reported after the exploitation of implicit user feedback, while an improved ranking is presented in most of the evaluated queries by visual example.