Bibtex de la publication

@InProceedings{ Mi2013.1,
author = {Mitran, Madalina and Mihalcea, Rada and Cabanac, Guillaume and Boughanem, Mohand},
title = "{Landmark Image Annotation Using Textual and Geolocation Metadata (short paper)}",
booktitle = "{Open Areas in Information Retrieval (OAIR), Lisbon, Portugal, 22/05/2013-24/05/2013}",
editor = {Calado, Pável and Metzler, Don and Sakai, Tetsuya and , },
year = {2013},
month = {mai},
publisher = {Centre de hautes études internationales d'Informatique Documentaire (C.I.D.)},
address = {http://www.le-cid.org},
pages = {65--68},
language = {anglais},
URL = {http://doi.acm.org/10.1145/2491765%20 - http://oatao.univ-toulouse.fr/12386/},
abstract = {In this paper, we address the problem of landmark image annotation, defined as the task of automatically annotating a landmark query image with relevant descriptors (keywords or tags). Given a new query image along with its geolocation metadata (latitude and longitude), we retrieve several other images already available in a community image database (e.g., flickr.com, panoramio.com), found within a fixed radius of the location of the query image. We then formulate the automatic landmark image annotation problem as a tag ranking problem over all the tags obtained from these pre-existing neighboring images. We propose several tag ranking factors, and by evaluating them against a gold standard constructed using the geolocation-oriented photo sharing platform panoramio.com, we show that an aggregated measure that combines both distance and frequency factors leads to results significantly better than any of the individual factors}
}