Artikel in Tagungsbänden
Summary of the 15th Discovery Challenge: Recommending Given Names.
In:
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, Band 1120, Seiten 7-24.
CEUR-WS, Aachen, Germany, 2014.
Folke Mitzlaff, Stephan Doerfel, Andreas Hotho, Robert Jäschke und Juergen Mueller.
[doi]
[Kurzfassung]
[BibTeX]
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.
Tag Recommendations for SensorFolkSonomies.
In:
Recommender Systems and the Social Web Workshop at 7th ACM Conference on Recommender Systems, RecSys 2013, Hong Kong, China - October 12-16, 2013. Proceedings, Seiten New York, NY, USA.
ACM, 2013.
accepted for publication
Juergen Mueller, Stephan Doerfel, Martin Becker, Andreas Hotho und Gerd Stumme.
[Kurzfassung]
[BibTeX]
With the rising popularity of smart mobile devices, sensor data-based applications have become more and more popular. Their users record data during their daily routine or specifically for certain events. The application WideNoise Plus allows users to record sound samples and to annotate them with perceptions and tags. The app is being used to document and map the soundscape all over the world. The procedure of recording, including the assignment of tags, has to be as easy-to-use as possible. We therefore discuss the application of tag recommender algorithms in this particular scenario. We show, that this task is fundamentally different from the well-known tag recommendation problem in folksonomies as users do no longer tag fix resources but rather sensory data and impressions. The scenario requires efficient recommender algorithms that are able to run on the mobile device, since Internet connectivity cannot be assumed to be available. Therefore, we evaluate the performance of several tag recommendation algorithms and discuss their applicability in the mobile sensing use-case.
Tag Recommendations for SensorFolkSonomies.
In:
Recommender Systems and the Social Web Workshop at 7th ACM Conference on Recommender Systems, RecSys 2013, Hong Kong, China - October 12-16, 2013. Proceedings, Band 1066.
CEUR-WS, Aachen, Germany, 2013.
Juergen Mueller, Stephan Doerfel, Martin Becker, Andreas Hotho und Gerd Stumme.
[doi]
[Kurzfassung]
[BibTeX]
With the rising popularity of smart mobile devices, sensor data-based applications have become more and more popular. Their users record data during their daily routine or specifically for certain events. The application WideNoise Plus allows users to record sound samples and to annotate them with perceptions and tags. The app is being used to document and map the soundscape all over the world. The procedure of recording, including the assignment of tags, has to be as easy-to-use as possible. We therefore discuss the application of tag recommender algorithms in this particular scenario. We show, that this task is fundamentally different from the well-known tag recommendation problem in folksonomies as users do no longer tag fix resources but rather sensory data and impressions. The scenario requires efficient recommender algorithms that are able to run on the mobile device, since Internet connectivity cannot be assumed to be available. Therefore, we evaluate the performance of several tag recommendation algorithms and discuss their applicability in the mobile sensing use-case.
Tag Recommendations for SensorFolkSonomies.
In:
Recommender Systems and the Social Web Workshop at 7th ACM Conference on Recommender Systems, RecSys 2013, Hong Kong, China - October 12-16, 2013. Proceedings, Seiten New York, NY, USA.
ACM, 2013.
accepted for publication
Juergen Mueller, Stephan Doerfel, Martin Becker, Andreas Hotho und Gerd Stumme.
[Kurzfassung]
[BibTeX]
With the rising popularity of smart mobile devices, sensor data-based applications have become more and more popular. Their users record data during their daily routine or specifically for certain events. The application WideNoise Plus allows users to record sound samples and to annotate them with perceptions and tags. The app is being used to document and map the soundscape all over the world. The procedure of recording, including the assignment of tags, has to be as easy-to-use as possible. We therefore discuss the application of tag recommender algorithms in this particular scenario. We show, that this task is fundamentally different from the well-known tag recommendation problem in folksonomies as users do no longer tag fix resources but rather sensory data and impressions. The scenario requires efficient recommender algorithms that are able to run on the mobile device, since Internet connectivity cannot be assumed to be available. Therefore, we evaluate the performance of several tag recommendation algorithms and discuss their applicability in the mobile sensing use-case.