TY - CONF AU - Mueller, Juergen AU - Doerfel, Stephan AU - Becker, Martin AU - Hotho, Andreas AU - Stumme, Gerd A2 - T1 - Tag Recommendations for SensorFolkSonomies T2 - Recommender Systems and the Social Web Workshop at 7th ACM Conference on Recommender Systems, RecSys 2013, Hong Kong, China -- October 12-16, 2013. Proceedings PB - ACM C1 - PY - 2013/ CY - VL - IS - SP - EP - UR - DO - KW - 2013 KW - RecSys KW - everyaware KW - folksonomy KW - myown KW - recommendation KW - rsweb KW - sensor KW - tag KW - widenoise L1 - SN - N1 - N1 - AB - 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. ER -