Summary of the 15th Discovery Challenge: Recommending Given Names
F. Mitzlaff, S. Doerfel, A. Hotho, R. Jäschke, and J. Mueller. 15th Discovery Challenge of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2013, Prague, Czech Republic - Sctober 27, 2013. Proceedings, 1120, page 7--24. Aachen, Germany, CEUR-WS, (2014)
Abstract
The 15th ECML PKDD Discovery Challenge centered around the recommendation
of given names. Participants of the challenge implemented algorithms
that were tested both offline - on data collected by the name search
engine Nameling - and online within Nameling. Here, we describe both
tasks in detail and discuss the publicly available datasets. We motivate
and explain the chosen evaluation of the challenge, and we summarize
the different approaches applied to the name recommendation tasks.
Finally, we present the rankings and winners of the offline and the
online phase.
15th Discovery Challenge of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2013, Prague, Czech Republic - Sctober 27, 2013. Proceedings
%0 Conference Paper
%1 mueller-2014a
%A Mitzlaff, Folke
%A Doerfel, Stephan
%A Hotho, Andreas
%A Jäschke, Robert
%A Mueller, Juergen
%B 15th Discovery Challenge of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2013, Prague, Czech Republic - Sctober 27, 2013. Proceedings
%C Aachen, Germany
%D 2014
%I CEUR-WS
%K 2014 CUER-WS ECMLPKDD InProceedings KDE LUH Nameling RecSys myown workshop
%P 7--24
%T Summary of the 15th Discovery Challenge: Recommending Given Names
%U http://ceur-ws.org/Vol-1120/paper1.pdf
%V 1120
%X The 15th ECML PKDD Discovery Challenge centered around the recommendation
of given names. Participants of the challenge implemented algorithms
that were tested both offline - on data collected by the name search
engine Nameling - and online within Nameling. Here, we describe both
tasks in detail and discuss the publicly available datasets. We motivate
and explain the chosen evaluation of the challenge, and we summarize
the different approaches applied to the name recommendation tasks.
Finally, we present the rankings and winners of the offline and the
online phase.
@inproceedings{mueller-2014a,
abstract = {The 15th ECML PKDD Discovery Challenge centered around the recommendation
of given names. Participants of the challenge implemented algorithms
that were tested both offline - on data collected by the name search
engine Nameling - and online within Nameling. Here, we describe both
tasks in detail and discuss the publicly available datasets. We motivate
and explain the chosen evaluation of the challenge, and we summarize
the different approaches applied to the name recommendation tasks.
Finally, we present the rankings and winners of the offline and the
online phase.},
added-at = {2018-08-30T12:20:30.000+0200},
address = {Aachen, Germany},
author = {Mitzlaff, Folke and Doerfel, Stephan and Hotho, Andreas and Jäschke, Robert and Mueller, Juergen},
biburl = {https://www.bibsonomy.org/bibtex/2e279965dffa803ee660e4026fe48340a/kde-alumni},
booktitle = {15th Discovery Challenge of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2013, Prague, Czech Republic - Sctober 27, 2013. Proceedings},
interhash = {6945009ac2fd770a84c47f2a0e192802},
intrahash = {e279965dffa803ee660e4026fe48340a},
issn = {1613-0073},
keywords = {2014 CUER-WS ECMLPKDD InProceedings KDE LUH Nameling RecSys myown workshop},
pages = {7--24},
publisher = {CEUR-WS},
timestamp = {2018-08-30T12:20:30.000+0200},
title = {Summary of the 15th Discovery Challenge: Recommending Given Names},
url = {http://ceur-ws.org/Vol-1120/paper1.pdf},
volume = 1120,
year = 2014
}