mendation service which can be called via HTTP by BibSonomy's recommender when a user posts a bookmark or publication. All participating recommenders are called on each posting process, one of them is choosen to actually deliver the results to the user. We can then measure
Herzlich Willkommen in Gnod's Musikwelt... Selbst wenn Du nicht weißt, was Du suchst - Gnod findet es. Im Internet liegt Dir die Welt der Musik zu Füßen, doch Dir fällt manchmal gar nicht ein, was Dir noch gefallen könnte ? Jetzt kommt Gnod ins Spiel
We just presented yesterday at ISMIR a tutorial about Linked Data for music-related information. More information on the tutorial is available on the tutorial website, and the
Online photo services such as Flickr and Zooomr allow users
to share their photos with family, friends, and the online
community at large. An important facet of these services
is that users manually annotate their photos using so called
tags, which describe the contents of the photo or provide
additional contextual and semantical information. In this
paper we investigate how we can assist users in the tagging
phase. The contribution of our research is twofold. We
analyse a representative snapshot of Flickr and present the
results by means of a tag characterisation focussing on how
users tags photos and what information is contained in the
tagging. Based on this analysis, we present and evaluate tag
recommendation strategies to support the user in the photo
annotation task by recommending a set of tags that can be
added to the photo. The results of the empirical evaluation
show that we can effectively recommend relevant tags for a
variety of photos with different levels of exhaustiveness of
original tagging.
Our main goal is to provide you with data because you know what you want to do with it. Still, we give some information regarding typical MIR tasks below. We hope to provide snippets of code and benchmarks results to help you getting started. If you want to provide additional information / link to your code / new results / new tasks, please send us an email! We also try to maintain an informal list of publications that use the dataset.
Y. Su, R. Zhang, S. Erfani, and J. Gan. Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, ACM, (July 2021)
K. Kobs, T. Koopmann, A. Zehe, D. Fernes, P. Krop, and A. Hotho. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: Findings, page 878--883. Online, Association for Computational Linguistics, (November 2020)