UPMC at MediaEval 2016 Retrieving Diverse Social Images Task

Sabrina Tollari 1
1 LFI - Learning, Fuzzy and Intelligent systems
LIP6 - Laboratoire d'Informatique de Paris 6
Abstract : In the MediaEval 2016 Retrieving Diverse Social Images Task, we proposed a general framework based on agglomerative hierarchical clustering (AHC). We tested the provided credibility descriptors as a vector input for our AHC. The results on devset showed that this vector based on the credibility descriptors is the best feature, but unfortunately that is not confirmed on testset. To merge several features, we chose to merge feature similarities. Tests on devset showed that to merge similarities using linear or weighted-max operators gave, most of the time, better results than using only one feature. This results is partially confirmed on testset.
Document type :
Conference papers
Liste complète des métadonnées

Cited literature [5 references]  Display  Hide  Download

https://hal.sorbonne-universite.fr/hal-01395045
Contributor : Sabrina Tollari <>
Submitted on : Monday, November 14, 2016 - 4:56:54 PM
Last modification on : Thursday, March 21, 2019 - 1:14:09 PM
Document(s) archivé(s) le : Wednesday, March 15, 2017 - 4:28:16 AM

File

Tollari_MediaEval_2016.pdf
Publisher files allowed on an open archive

Identifiers

  • HAL Id : hal-01395045, version 1

Citation

Sabrina Tollari. UPMC at MediaEval 2016 Retrieving Diverse Social Images Task. MediaEval 2016 Workshop, Oct 2016, Hilversum, Netherlands. ⟨hal-01395045⟩

Share

Metrics

Record views

102

Files downloads

51