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
This year's discovery challenge presents two tasks in the new area
of social bookmarking. One task covers spam detection and
the other covers tag recommendations. As we are hosting the social bookmark and
publication sharing system BibSonomy, we are able to provide a dataset
of BibSonomy for the challenge. A training dataset for both tasks is provided at the beginning of the competition.
The test dataset will be released 48 hours before the final deadline. Due to a very tight schedule we cannot grant any deadline
extension.
The presentation of the results will take place at the ECML/PKDD workshop where the top teams are
invited to present their approaches and results.
M. Atzmueller, и B. Kloepper. Proc. International Conference on Intelligent Data Engineering and Automated Learning, Workshop on Methods for Interpretation of Industrial Event Logs, Heidelberg, Germany, Springer Verlag, ((accepted) 2018)
A. Hendrickson, J. Wang, и M. Atzmueller. Proc. 24th International Symposium on Methodologies for Intelligent Systems (ISMIS), Heidelberg, Germany, Springer Verlag, ((accepted) 2018)
E. Sternberg, и M. Atzmueller. Proc. 24th International Symposium on Methodologies for Intelligent Systems (ISMIS), Heidelberg, Germany, Springer Verlag, ((accepted) 2018)
L. Rombout, M. Atzmueller, и M. Postma. Proc. Workshop on Affective Computing and Context Awareness in Ambient Intelligence, UPV, Valencia, Spain, (2018)