@misc{KliemeTietzMeinel2018,
  author    = {Klieme, Eric and Tietz, Christian and Meinel, Christoph},
  title     = {Beware of SMOMBIES},
  series = {The 17th IEEE International Conference on Trust, Security and Privacy in Computing and Communications (IEEE TrustCom 2018)/the 12th IEEE International Conference on Big Data Science and Engineering (IEEE BigDataSE 2018)},
  journal   = {The 17th IEEE International Conference on Trust, Security and Privacy in Computing and Communications (IEEE TrustCom 2018)/the 12th IEEE International Conference on Big Data Science and Engineering (IEEE BigDataSE 2018)},
  publisher = {IEEE},
  address   = {New York},
  isbn      = {978-1-5386-4387-7},
  issn      = {2324-9013},
  doi       = {10.1109/TrustCom/BigDataSE.2018.00096},
  pages     = {651 -- 660},
  year      = {2018},
  abstract  = {Several research evaluated the user's style of walking for the verification of a claimed identity and showed high authentication accuracies in many settings. In this paper we present a system that successfully verifies a user's identity based on many real world smartphone placements and yet not regarded interactions while walking. Our contribution is the distinction of all considered activities into three distinct subsets and a specific one-class Support Vector Machine per subset. Using sensor data of 30 participants collected in a semi-supervised study approach, we prove that unsupervised verification is possible with very low false-acceptance and false-rejection rates. We furthermore show that these subsets can be distinguished with a high accuracy and demonstrate that this system can be deployed on off-the-shelf smartphones.},
  language  = {en}
}
@article{MeinelWang2006,
  author    = {Meinel, Christoph and Wang, Long},
  title     = {Building content clusters based on modelling page pairs},
  doi       = {10.1007/11610113_85},
  year      = {2006},
  abstract  = {We give a new view on building content clusters from page pair models. We measure the heuristic importance within every two pages by computing the distance of their accessed positions in usage sessions. We also compare our page pair models with the classical pair models used in information theories and natural language processing, and give different evaluation methods to build the reasonable content communities. And we finally interpret the advantages and disadvantages of our models from detailed experiment results},
  language  = {en}
}
@article{LindbergMeinelWagner2011,
  author    = {Lindberg, Tilmann and Meinel, Christoph and Wagner, Ralf},
  title     = {Design thinking : a fruitful concept for IT development?},
  isbn      = {978-3-642-13756-3},
  year      = {2011},
  language  = {en}
}
@article{MeinelLeifer2012,
  author    = {Meinel, Christoph and Leifer, Larry},
  title     = {Design thinking research},
  isbn      = {978-3-642-31990-7},
  year      = {2012},
  language  = {en}
}
@article{MeinelLeifer2011,
  author    = {Meinel, Christoph and Leifer, Larry},
  title     = {Design thinking research},
  isbn      = {978-3-642-13756-3},
  year      = {2011},
  language  = {en}
}
@article{MeinelLeifer2012,
  author    = {Meinel, Christoph and Leifer, Larry},
  title     = {Design thinking research},
  year      = {2012},
  language  = {en}
}
@misc{AlhosseiniAlmodarresiYasinBinTareafNajafietal.2019,
  author    = {Alhosseini Almodarresi Yasin, Seyed Ali and Bin Tareaf, Raad and Najafi, Pejman and Meinel, Christoph},
  title     = {Detect me if you can},
  series = {Companion Proceedings of The 2019 World Wide Web Conference},
  journal   = {Companion Proceedings of The 2019 World Wide Web Conference},
  publisher = {Association for Computing Machinery},
  address   = {New York},
  isbn      = {978-1-4503-6675-5},
  doi       = {10.1145/3308560.3316504},
  pages     = {148 -- 153},
  year      = {2019},
  abstract  = {Spam Bots have become a threat to online social networks with their malicious behavior, posting misinformation messages and influencing online platforms to fulfill their motives. As spam bots have become more advanced over time, creating algorithms to identify bots remains an open challenge. Learning low-dimensional embeddings for nodes in graph structured data has proven to be useful in various domains. In this paper, we propose a model based on graph convolutional neural networks (GCNN) for spam bot detection. Our hypothesis is that to better detect spam bots, in addition to defining a features set, the social graph must also be taken into consideration. GCNNs are able to leverage both the features of a node and aggregate the features of a node's neighborhood. We compare our approach, with two methods that work solely on a features set and on the structure of the graph. To our knowledge, this work is the first attempt of using graph convolutional neural networks in spam bot detection.},
  language  = {en}
}
@book{MeinelSack2009,
  author    = {Meinel, Christoph and Sack, Harald},
  title     = {Digitale Kommunikation : Vernetzen, Multimedia, Sicherheit},
  series = {Media Press},
  journal   = {Media Press},
  publisher = {Springer-Verlag Berlin Heidelberg},
  address   = {Berlin, Heidelberg},
  isbn      = {978-3-540-92922-2},
  issn      = {1439-3107},
  doi       = {10.1007/978-3-540-92923-9},
  pages     = {422 S.},
  year      = {2009},
  language  = {de}
}
@book{LinckelsMeinel2011,
  author    = {Linckels, Serge and Meinel, Christoph},
  title     = {E-Librarian service : user-friendly semantic search in digital libraries},
  publisher = {Springer-Verlag Berlin Heidelberg},
  address   = {Berlin, Heidelberg},
  isbn      = {978-3-642-17742-2},
  doi       = {10.1007/978-3-642-17743-9},
  pages     = {212 S.},
  year      = {2011},
  language  = {en}
}
@article{ThienenNoweskiRauthetal.2012,
  author    = {Thienen, Julia von and Noweski, Christine and Rauth, Ingo and Meinel, Christoph and Lange, Sabine},
  title     = {If you want to know who are, tell me where you are : the importance of places},
  year      = {2012},
  language  = {en}
}