A Ranking based Model for Automatic Annotation in a Social Network

Ludovic Denoyer 1 Patrick Gallinari 1
1 MALIRE - Machine Learning and Information Retrieval
LIP6 - Laboratoire d'Informatique de Paris 6
Abstract : We propose a relational ranking model for learning to tag images in social media sharing systems. This model learns to associate a ranked list of tags to unlabeled images, by considering simultaneously content information (visual or textual) and relational information among the images. It is able to handle implicit relations like content similarities, and explicit ones like friendship or authorship. The model itself is based on a transductive algorithm thats learns from both labeled and unlabeled data. Experiments on a real corpus extracted from Flickr show the effectiveness of this model.
Document type :
Conference papers
Complete list of metadatas

Contributor : Lip6 Publications <>
Submitted on : Tuesday, March 22, 2016 - 3:04:45 PM
Last modification on : Thursday, March 21, 2019 - 1:04:53 PM


  • HAL Id : hal-01292064, version 1


Ludovic Denoyer, Patrick Gallinari. A Ranking based Model for Automatic Annotation in a Social Network. The Fourth International AAAI Conference on Weblogs and Social Media, ICWSM 2010, May 2010, Washington, DC, United States. pp.231-234. ⟨hal-01292064⟩



Record views