J. Mueller, S. Doerfel, M. Becker, A. Hotho, и G. Stumme. Recommender Systems and the Social Web Workshop at 7th ACM Conference on Recommender Systems, RecSys 2013, Hong Kong, China -- October 12-16, 2013. Proceedings, стр. New York, NY, USA. ACM, (2013)accepted for publication.
Аннотация
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.
Recommender Systems and the Social Web Workshop at 7th ACM Conference on Recommender Systems, RecSys 2013, Hong Kong, China -- October 12-16, 2013. Proceedings
%0 Conference Paper
%1 mueller2013recommendations
%A Mueller, Juergen
%A Doerfel, Stephan
%A Becker, Martin
%A Hotho, Andreas
%A Stumme, Gerd
%B Recommender Systems and the Social Web Workshop at 7th ACM Conference on Recommender Systems, RecSys 2013, Hong Kong, China -- October 12-16, 2013. Proceedings
%D 2013
%I ACM
%K 2013 RecSys everyaware folksonomy iteg itegpub l3s myown recommendation rsweb sensor sitc tag widenoise
%P New York, NY, USA
%T Tag Recommendations for SensorFolkSonomies
%X 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.
@inproceedings{mueller2013recommendations,
abstract = {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.},
added-at = {2013-12-16T17:19:49.000+0100},
author = {Mueller, Juergen and Doerfel, Stephan and Becker, Martin and Hotho, Andreas and Stumme, Gerd},
biburl = {https://www.bibsonomy.org/bibtex/26190d6064dfdb3b8d71f2898539e993e/stumme},
booktitle = {Recommender Systems and the Social Web Workshop at 7th ACM Conference on Recommender Systems, RecSys 2013, Hong Kong, China -- October 12-16, 2013. Proceedings},
interhash = {23d1cf49208d9a0c8b883dc69d4e444d},
intrahash = {6190d6064dfdb3b8d71f2898539e993e},
keywords = {2013 RecSys everyaware folksonomy iteg itegpub l3s myown recommendation rsweb sensor sitc tag widenoise},
note = {accepted for publication},
pages = {New York, NY, USA},
publisher = {ACM},
timestamp = {2015-03-25T13:26:13.000+0100},
title = {Tag Recommendations for SensorFolkSonomies},
year = 2013
}