@inproceedings{mitzlaff2014summary,
  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.},
  address = {Aachen, Germany},
  author = {Mitzlaff, Folke and Doerfel, Stephan and Hotho, Andreas and Jäschke, Robert and Mueller, Juergen},
  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},
  pages = {7--24},
  publisher = {CEUR-WS},
  title = {Summary of the 15th Discovery Challenge: Recommending Given Names},
  url = {http://ceur-ws.org/Vol-1120/},
  volume = 1120,
  year = 2014
}

@inproceedings{becker2013generic,
  abstract = {An increasing number of platforms like Xively or ThingSpeak are available to manage ubiquitous sensor data enabling the Internet of Things. Strict data formats allow interoperability and informative visualizations, supporting the development of custom user applications. Yet, these strict data formats as well as the common feed-centric approach limit the flexibility of these platforms. We aim at providing a concept that supports data ranging from text-based formats like JSON to images and video footage. Furthermore, we introduce the concept of extensions, which allows to enrich existing data points with additional information, thus, taking a data point centric approach. This enables us to gain semantic and user specific context by attaching subjective data to objective values. This paper provides an overview of our architecture including concept, implementation details and present applications. We distinguish our approach from several other systems and describe two sensing applications namely AirProbe and WideNoise that were implemented for our platform.},
  address = {New York, NY, USA},
  author = {Becker, Martin and Mueller, Juergen and Hotho, Andreas and Stumme, Gerd},
  booktitle = {1st International Workshop on Pervasive Urban Crowdsensing Architecture and Applications, PUCAA 2013, Zurich, Switzerland -- September 9, 2013. Proceedings},
  doi = {10.1145/2494091.2499776},
  interhash = {5302866e7849d40a44deab166b6c4d36},
  intrahash = {35eef1ecdac9d83d3bfbcac22c31984a},
  pages = {1175--1182},
  publisher = {ACM},
  title = {A Generic Platform for Ubiquitous and Subjective Data},
  year = 2013
}

@inproceedings{atzmueller2013subgroup,
  abstract = {This paper applies subgroup discovery for obtaining interesting descriptive
 patterns in ubiquitous data. Furthermore, we provide a novel graph-based
 analysis approach for assessing the relations between the obtained
 subgroup set, and for ranking subgroups according to their relationships
 to other subgroups. We present and discuss first results utilizing
 real-world data, given by noise measurements with associated subjective
 perceptions and a set of tags describing the semantic context.},
  address = {Kassel, Germany},
  author = {Atzmueller, Martin and Mueller, Juergen},
  booktitle = {Mining Ubiquitous and Social Environments Workshop at European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECMLPKDD 2013, Prague, Czech Republic -- September 23-27, 2013. Proceedings},
  interhash = {339aa18b5a6047ea4005f6c6a48b9bb6},
  intrahash = {72d80f820d7cd8bc00469bc5ea3ed534},
  pages = {19--27},
  title = {Subgroup Analytics and Interactive Assessment on Ubiquitous Data},
  url = {http://www.kde.cs.uni-kassel.de/ws/muse2013/#proceedings},
  year = 2013
}

@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.},
  address = {Aachen, Germany},
  author = {Mueller, Juergen and Doerfel, Stephan and Becker, Martin and Hotho, Andreas and Stumme, Gerd},
  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 = {2bab3f013052bc741e795c5c61aea5c9},
  issn = {1613-0073},
  publisher = {CEUR-WS},
  title = {Tag Recommendations for SensorFolkSonomies},
  url = {http://ceur-ws.org/Vol-1066/},
  volume = 1066,
  year = 2013
}

@inproceedings{mueller-2012,
  abstract = {The connection of ubiquitous and social computing is an emerging research
 area which is combining two prominent areas of computer science.
 In this paper, we tackle this topic from different angles: We describe
 data mining methods for ubiquitous and social data, specifically
 focusing on physical and social activities, and provide exemplary
 analysis results. Furthermore, we give an overview on the Ubicon
 platform which provides a framework for the creation and hosting
 of ubiquitous and social applications for diverse tasks and projects.
 Ubicon features the collection and analysis of both physical and
 social activities of users for enabling inter-connected applications
 in ubiquitous and social contexts. We summarize three real-world
 systems built on top of Ubicon, and exemplarily discuss the according
 mining and analysis aspects.},
  address = {Washington, DC, USA},
  author = {Atzmueller, Martin and Becker, Martin and Doerfel, Stephan and Kibanov, Mark and Hotho, Andreas and Macek, Björn-Elmar and Mitzlaff, Folke and Mueller, Juergen and Scholz, Christoph and Stumme, Gerd},
  booktitle = {IEEE International Conference on Cyber, Physical and Social Computing, CPSCom 2012, Besançon, France, 20-23 November, 2012},
  interhash = {a2695fd9fe6e76b252edbd42d72b34ad},
  intrahash = {90847b1d969ac1ed1f4c8d7146416619},
  publisher = {IEEE},
  title = {Ubicon: Observing Social and Physical Activities},
  year = 2012
}