@article{hotho2010ubiquitous,
  author = {Hotho, Andreas and {Ulslev Pedersen}, Rasmus and Wurst, Michael},
  interhash = {e779fb5dff41b65bce1aa38fdca4a376},
  intrahash = {56f2940d5d0f2ce59c342d3b8ad42ca1},
  issn = {0302-9743},
  journal = {Lecture Notes in Computer Science},
  number = 6202,
  pages = {61--74},
  publisher = {Springer},
  title = {Ubiquitous Data},
  url = {http://rd.springer.com/content/pdf/10.1007%2F978-3-642-16392-0_4.pdf},
  year = 2010
}

@article{morstatter2013sample,
  author = {Morstatter, Fred and {\"u}rgen Pfeffer, J and Liu, Huan and Carley, Kathleen M},
  interhash = {bca742d25a5f5fa43c8f106460449b5b},
  intrahash = {58707a28cc5098b9b3444501d5ca9a88},
  title = {Is the Sample Good Enough? Comparing Data from Twitter’s Streaming API with Twitter’s Firehose},
  url = {http://scholar.google.de/scholar.bib?q=info:NkS2afIrqyQJ:scholar.google.com/&output=citation&hl=de&as_sdt=0,5&ct=citation&cd=0},
  year = 2013
}

@article{RePEc:eee:csdana:v:41:y:2002:i:1:p:59-90,
  abstract = {No abstract is available for this item.},
  author = {Dhillon, Inderjit S. and Modha, Dharmendra S. and Spangler, W. Scott},
  interhash = {3ff82dddf6ce4d86909347824554ddf8},
  intrahash = {03e92f40796a0093a6e882a83f5cd995},
  journal = {Computational Statistics \& Data Analysis},
  month = {November},
  number = 1,
  pages = {59-90},
  title = {Class visualization of high-dimensional data with applications},
  url = {http://www.cs.utexas.edu/~inderjit/public_papers/csda.pdf},
  volume = 41,
  year = 2002
}

@inproceedings{bullock2011tagging,
  author = {Bullock, Beate Navarro and Jäschke, Robert and Hotho, Andreas},
  booktitle = {Proceedings of the ACM WebSci'11},
  interhash = {7afaa67dfeb07f7e0b85abf2be61aff1},
  intrahash = {493e03868a98f498628cad31f9320e9f},
  month = {June},
  title = {Tagging data as implicit feedback for learning-to-rank},
  url = {http://journal.webscience.org/463/},
  year = 2011
}

@article{Song19022010,
  abstract = {A range of applications, from predicting the spread of human and electronic viruses to city planning and resource management in mobile communications, depend on our ability to foresee the whereabouts and mobility of individuals, raising a fundamental question: To what degree is human behavior predictable? Here we explore the limits of predictability in human dynamics by studying the mobility patterns of anonymized mobile phone users. By measuring the entropy of each individual’s trajectory, we find a 93% potential predictability in user mobility across the whole user base. Despite the significant differences in the travel patterns, we find a remarkable lack of variability in predictability, which is largely independent of the distance users cover on a regular basis.},
  author = {Song, Chaoming and Qu, Zehui and Blumm, Nicholas and Barabási, Albert-László},
  doi = {10.1126/science.1177170},
  eprint = {http://www.sciencemag.org/content/327/5968/1018.full.pdf},
  interhash = {f2611a08bf6db54f86e884c05f3cb5fb},
  intrahash = {a89330f8eb32ce62b5f5c9a2b4909f25},
  journal = {Science},
  number = 5968,
  pages = {1018-1021},
  title = {Limits of Predictability in Human Mobility},
  url = {http://www.sciencemag.org/content/327/5968/1018.abstract},
  volume = 327,
  year = 2010
}

@inproceedings{atze09,
  address = {Krakow, Poland},
  author = {Atzmueller, Martin and Lemmerich, Florian and Krause, Beate and Hotho, Andreas},
  booktitle = {7th Conference on Computer Methods and Systems},
  interhash = {c226a55c0cc2dc6f261b86c09225c260},
  intrahash = {014dbd07807e05a5ea9aafb2dbead39b},
  month = {November},
  note = {ISBN 83-916420-5-4},
  title = {Who are the Spammers? Understandable Local Patterns for Concept Description},
  url = {http://www.cms.agh.edu.pl/},
  year = 2009
}

@inproceedings{ALKH:09,
  author = {Atzmueller, Martin and Lemmerich, Florian and Krause, Beate and Hotho, Andreas},
  booktitle = {Proc. LeGo-09: From Local Patterns to Global Models, Workshop at the 2009 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
  editor = {Knobbe, Johannes F\"urnkranz Arno},
  interhash = {d27cd7eee4ab571ad3753a3d370141ce},
  intrahash = {bb80bdcc06c8886968c453fd920dfe05},
  note = {accepted},
  title = {{Towards Understanding Spammers - Discovering Local Patterns for Concept Characterization and Description}},
  url = {http://www.ke.tu-darmstadt.de/events/LeGo-09/04-Atzmueller.pdf},
  year = 2009
}

@inproceedings{anti2008krause,
  address = {New York, NY, USA},
  author = {Krause, Beate and Schmitz, Christoph and Hotho, Andreas and Stumme, Gerd},
  booktitle = {AIRWeb '08: Proceedings of the 4th international workshop on Adversarial information retrieval on the web},
  doi = {http://doi.acm.org/10.1145/1451983.1451998},
  interhash = {a45d40ac7776551301ad9dde5b25357f},
  intrahash = {68effe5d4b9460f9388e7685310f74c2},
  isbn = {978-1-60558-159-0},
  location = {Beijing, China},
  pages = {61--68},
  publisher = {ACM},
  title = {The Anti-Social Tagger - Detecting Spam in Social Bookmarking Systems},
  url = {http://airweb.cse.lehigh.edu/2008/submissions/krause_2008_anti_social_tagger.pdf},
  year = 2008
}

@incollection{books/mit/fayyadPSU96/FayyadPS96,
  author = {Fayyad, Usama M. and Piatetsky-Shapiro, Gregory and Smyth, Padhraic},
  booktitle = {Advances in Knowledge Discovery and Data Mining},
  date = {2002-01-03},
  interhash = {79663e4b1f464b82ce1ae45345dc424f},
  intrahash = {e59886c68d1fc9bb4d1a8d6a1a644a60},
  pages = {1-34},
  title = {From Data Mining to Knowledge Discovery: An Overview.},
  url = {http://dblp.uni-trier.de/db/books/collections/fayyad96.html#FayyadPS96},
  year = 1996
}

@article{romero07,
  abstract = {Currently there is an increasing interest in data mining and educational systems, making educational data mining as a new growing research community. This paper surveys the application of data mining to traditional educational systems, particular web-based courses, well-known learning content management systems, and adaptive and intelligent web-based educational systems. Each of these systems has different data source and objectives for knowledge discovering. After preprocessing the available data in each case, data mining techniques can be applied: statistics and visualization; clustering, classification and outlier detection; association rule mining and pattern mining; and text mining. The success of the plentiful work needs much more specialized work in order for educational data mining to become a mature area.},
  address = {Tarrytown, NY, USA},
  author = {Romero, C. and Ventura, S.},
  doi = {http://dx.doi.org/10.1016/j.eswa.2006.04.005},
  interhash = {89d843f1a3b181f2a628e881d9210b22},
  intrahash = {746d12e92e58587461ffcb8dc381e283},
  issn = {0957-4174},
  journal = {Expert Syst. Appl.},
  number = 1,
  pages = {135--146},
  publisher = {Pergamon Press, Inc.},
  title = {Educational data mining: A survey from 1995 to 2005},
  url = {http://portal.acm.org/citation.cfm?id=1223659},
  volume = 33,
  year = 2007
}