J. Mueller, S. Doerfel, M. Becker, A. Hotho, and G. Stumme. Proceedings of the Fifth ACM RecSys Workshop on Recommender Systems and the Social Web co-located with the 7th ACM Conference on Recommender Systems (RecSys 2013), CEUR-WS, (2013)
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.
Proceedings of the Fifth ACM RecSys Workshop on Recommender Systems and the Social Web co-located with the 7th ACM Conference on Recommender Systems (RecSys 2013)
%0 Conference Paper
%1 mueller2013tag
%A Mueller, Juergen
%A Doerfel, Stephan
%A Becker, Martin
%A Hotho, Andreas
%A Stumme, Gerd
%B Proceedings of the Fifth ACM RecSys Workshop on Recommender Systems and the Social Web co-located with the 7th ACM Conference on Recommender Systems (RecSys 2013)
%D 2013
%I CEUR-WS
%K diss:allmypubs eva21 folksonomy myown proposal recommendation sensor tag
%T Tag Recommendations for SensorFolkSonomies
%U http://ceur-ws.org/Vol-1066/Paper9.pdf
%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{mueller2013tag,
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 = {2013-12-31T18:16:10.000+0100},
author = {Mueller, Juergen and Doerfel, Stephan and Becker, Martin and Hotho, Andreas and Stumme, Gerd},
biburl = {https://www.bibsonomy.org/bibtex/2bbf2c8f4c5314838618b1063e057b6d1/becker},
booktitle = {Proceedings of the Fifth ACM RecSys Workshop on Recommender Systems and the Social Web co-located with the 7th ACM Conference on Recommender Systems (RecSys 2013)},
crossref = {conf/recsys/2013rsweb},
description = {impactfactor = {0.418},
impactfactor-year = 2013,
impactfactor-source = {https://www.scimagojr.com/journalsearch.php?q=21100218356&tip=sid}},
ee = {http://ceur-ws.org/Vol-1066/Paper9.pdf},
interhash = {23d1cf49208d9a0c8b883dc69d4e444d},
intrahash = {bbf2c8f4c5314838618b1063e057b6d1},
keywords = {diss:allmypubs eva21 folksonomy myown proposal recommendation sensor tag},
publisher = {CEUR-WS},
series = {CEUR Workshop Proceedings},
timestamp = {2022-02-22T00:10:18.000+0100},
title = {Tag Recommendations for SensorFolkSonomies},
url = {http://ceur-ws.org/Vol-1066/Paper9.pdf},
year = 2013
}