@inproceedings{vkistowski2015modeling,
  abstract = {Today’s system developers and operators face the challenge of creating software systems that make efficient use of dynamically allocated resources under highly variable and dynamic load profiles, while at the same time delivering reliable performance. Benchmarking of systems under these constraints is difficult, as state-of-the-art benchmarking frameworks provide only limited support for emulating such dynamic and highly vari- able load profiles for the creation of realistic workload scenarios. Industrial benchmarks typically confine themselves to workloads with constant or stepwise increasing loads. Alternatively, they support replaying of recorded load traces. Statistical load inten- sity descriptions also do not sufficiently capture concrete pattern load profile variations over time.
To address these issues, we present the Descartes Load Intensity Model (DLIM). DLIM provides a modeling formalism for describing load intensity variations over time. A DLIM instance can be used as a compact representation of a recorded load intensity trace, providing a powerful tool for benchmarking and performance analysis. As manually obtaining DLIM instances can be time consuming, we present three different automated extraction methods, which also help to enable autonomous system analysis for self-adaptive systems. Model expressiveness is validated using the presented extraction methods. Extracted DLIM instances exhibit a median modeling error of 12.4% on average over nine different real-world traces covering between two weeks and seven months. Additionally, extraction methods perform orders of magnitude faster than existing time series decomposition approaches.},
  author = {v. Kistowski, Jóakim and Nikolas, Herbst. and Zoller, Daniel and Kounev, Samuel and Hotho, Andreas},
  booktitle = {Proceedings of the 10th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS)},
  interhash = {9f0be929d7bcc057c778f6b44e73cf4c},
  intrahash = {f449d3cf35941636f96d72aaf620a275},
  title = {Modeling and Extracting Load Intensity Profiles},
  year = 2015
}

@inproceedings{zoller2015publication,
  abstract = {Scholarly success is traditionally measured in terms of citations to publications. With the advent of publication man- agement and digital libraries on the web, scholarly usage data has become a target of investigation and new impact metrics computed on such usage data have been proposed – so called altmetrics. In scholarly social bookmarking sys- tems, scientists collect and manage publication meta data and thus reveal their interest in these publications. In this work, we investigate connections between usage metrics and citations, and find posts, exports, and page views of publications to be correlated to citations.},
  author = {Zoller, Daniel and Doerfel, Stephan and Jäschke, Robert and Stumme, Gerd and Hotho, Andreas},
  booktitle = {Proceedings of the 2015 ACM Conference on Web Science},
  interhash = {3515b34cd19959cee5fafbf4467a75ed},
  intrahash = {548a7010ee2726f28e04e5c6e5fd6e2d},
  title = {On Publication Usage in a Social Bookmarking System},
  year = 2015
}

@inproceedings{dallmann2015media,
  address = {Cyprus, Turkey, September 1-4},
  author = {Dallmann, Alexander and Lemmerich, Florian and Zoller, Daniel and Hotho, Andreas},
  booktitle = {26th ACM Conference on Hypertext and Social Media},
  interhash = {6b2daa7830c5e504543dcdaefed46285},
  intrahash = {addfd0d84b4347392dc94a4bec400412},
  publisher = {ACM},
  title = {Media Bias in German Online Newspapers},
  year = 2015
}

@inproceedings{doerfel2014social,
  address = {New York, NY, USA},
  author = {Doerfel, Stephan and Zoller, Daniel and Singer, Philipp and Niebler, Thomas and Hotho, Andreas and Strohmaier, Markus},
  booktitle = {Proceedings of the 23rd International World Wide Web Conference},
  interhash = {9223d6d728612c8c05a80b5edceeb78b},
  intrahash = {11fab5468dd4b4e3db662ea5e68df8e0},
  publisher = {ACM},
  series = {WWW 2014},
  title = {How Social is Social Tagging?},
  year = 2014
}

@inproceedings{doerfel2014evaluating,
  author = {Doerfel, Stephan and Zoller, Daniel and Singer, Philipp and Niebler, Thomas and Hotho, Andreas and Strohmaier, Markus},
  bibsource = {dblp computer science bibliography, http://dblp.org},
  booktitle = {Proceedings of the 16th {LWA} Workshops: KDML, {IR} and FGWM, Aachen,               Germany, September 8-10, 2014.},
  editor = {Seidl, Thomas and Hassani, Marwan and Beecks, Christian},
  interhash = {955cd7c6f7652b7c531b699464925b1f},
  intrahash = {4b2e73c82b5a84e1959ad66aaad4a235},
  pages = {18--19},
  publisher = {CEUR-WS.org},
  title = {Evaluating Assumptions about Social Tagging - {A} Study of User Behavior
               in BibSonomy},
  url = {http://ceur-ws.org/Vol-1226/paper06.pdf},
  year = 2014
}

@inproceedings{doerfel2014evaluating,
  author = {Doerfel, Stephan and Zoller, Daniel and Singer, Philipp and Niebler, Thomas and Hotho, Andreas and Strohmaier, Markus},
  bibsource = {dblp computer science bibliography, http://dblp.org},
  booktitle = {Proceedings of the 16th {LWA} Workshops: KDML, {IR} and FGWM, Aachen,               Germany, September 8-10, 2014.},
  editor = {Seidl, Thomas and Hassani, Marwan and Beecks, Christian},
  interhash = {955cd7c6f7652b7c531b699464925b1f},
  intrahash = {4b2e73c82b5a84e1959ad66aaad4a235},
  pages = {18--19},
  publisher = {CEUR-WS.org},
  title = {Evaluating Assumptions about Social Tagging - {A} Study of User Behavior
               in BibSonomy},
  url = {http://ceur-ws.org/Vol-1226/paper06.pdf},
  year = 2014
}

@inproceedings{doerfel2014social,
  address = {New York, NY, USA},
  author = {Doerfel, Stephan and Zoller, Daniel and Singer, Philipp and Niebler, Thomas and Hotho, Andreas and Strohmaier, Markus},
  booktitle = {Proceedings of the 23rd International World Wide Web Conference},
  interhash = {9223d6d728612c8c05a80b5edceeb78b},
  intrahash = {11fab5468dd4b4e3db662ea5e68df8e0},
  publisher = {ACM},
  series = {WWW 2014},
  title = {How Social is Social Tagging?},
  year = 2014
}

@misc{doerfel2014course,
  abstract = {Social tagging systems have established themselves as an important part in
today's web and have attracted the interest from our research community in a
variety of investigations. The overall vision of our community is that simply
through interactions with the system, i.e., through tagging and sharing of
resources, users would contribute to building useful semantic structures as
well as resource indexes using uncontrolled vocabulary not only due to the
easy-to-use mechanics. Henceforth, a variety of assumptions about social
tagging systems have emerged, yet testing them has been difficult due to the
absence of suitable data. In this work we thoroughly investigate three
available assumptions - e.g., is a tagging system really social? - by examining
live log data gathered from the real-world public social tagging system
BibSonomy. Our empirical results indicate that while some of these assumptions
hold to a certain extent, other assumptions need to be reflected and viewed in
a very critical light. Our observations have implications for the design of
future search and other algorithms to better reflect the actual user behavior.},
  author = {Doerfel, Stephan and Zoller, Daniel and Singer, Philipp and Niebler, Thomas and Hotho, Andreas and Strohmaier, Markus},
  interhash = {65f287480af20fc407f7d26677f17b72},
  intrahash = {988ea3a9b85ec0656e27750e4080325c},
  note = {cite arxiv:1401.0629},
  title = {Of course we share! Testing Assumptions about Social Tagging Systems},
  url = {http://arxiv.org/abs/1401.0629},
  year = 2014
}

@techreport{doerfel2014course,
  abstract = {Social tagging systems have established themselves as an important part in
today's web and have attracted the interest from our research community in a
variety of investigations. The overall vision of our community is that simply
through interactions with the system, i.e., through tagging and sharing of
resources, users would contribute to building useful semantic structures as
well as resource indexes using uncontrolled vocabulary not only due to the
easy-to-use mechanics. Henceforth, a variety of assumptions about social
tagging systems have emerged, yet testing them has been difficult due to the
absence of suitable data. In this work we thoroughly investigate three
available assumptions - e.g., is a tagging system really social? - by examining
live log data gathered from the real-world public social tagging system
BibSonomy. Our empirical results indicate that while some of these assumptions
hold to a certain extent, other assumptions need to be reflected and viewed in
a very critical light. Our observations have implications for the design of
future search and other algorithms to better reflect the actual user behavior.},
  author = {Doerfel, Stephan and Zoller, Daniel and Singer, Philipp and Niebler, Thomas and Hotho, Andreas and Strohmaier, Markus},
  interhash = {65f287480af20fc407f7d26677f17b72},
  intrahash = {e360f0bd207806e72305efe16491ebe3},
  note = {cite arxiv:1401.0629},
  title = {Of course we share! Testing Assumptions about Social Tagging Systems},
  url = {http://arxiv.org/abs/1401.0629},
  year = 2014
}