TUW @ Retrieving Diverse Social Images Task 2014

Authors: 
João Palotti
Navid Rekabsaz
Mihai Lupu
Allan Hanbury
Type: 
Speech with proceedings
Proceedings: 
Working Notes Proceedings of the MediaEval 2014 Workshop
Publisher: 
CEUR-WS
Pages: 
ISBN: 
ISSN: 1613-0073
Year: 
2014
Abstract: 
This paper describes the e orts of Vienna University of Technology (TUW) in the MediaEval 2014 Retrieving Diverse Social Images challenge. Our approach consisted of 3 steps: (1)<br> a pre-filtering based on Machine Learning, (2) a re-ranking<br> based on Word2Vec, and (3) a clustering part based on an<br> ensemble of clusters. Our best run reached a F@20 of 0.564.
TU Focus: 
Information and Communication Technology
Reference: 

J. Palotti, N. Rekabsaz, M. Lupu, A. Hanbury:
"TUW @ Retrieving Diverse Social Images Task 2014";
Vortrag: MediaEval Benchmarking Initiative for Multimedia Evaluation, Barcelona, ES; 16.10.2014 - 17.10.2014; in: "Working Notes Proceedings of the MediaEval 2014 Workshop", CEUR-WS, Vol-1263 (2014), ISSN: 1613-0073.

Zusätzliche Informationen

Last changed: 
13.01.2015 17:31:36
TU Id: 
235956
Accepted: 
Accepted
Invited: 
Department Focus: 
Business Informatics
Abstract German: 
Author List: 
J. Palotti, N. Rekabsaz, M. Lupu, A. Hanbury