@book{janson2000theory,
  address = {New York; Chichester},
  author = {Janson, Svante and Luczak, Tomasz and Rucinski, Andrzej},
  interhash = {929294638db37c413b283ac468bbdade},
  intrahash = {7bb074240f72009f515123f15afecefd},
  isbn = {0471175412 9780471175414},
  publisher = {John Wiley & Sons},
  refid = {43340250},
  title = {Theory of random graphs},
  url = {http://www.amazon.com/Random-Graphs-Svante-Janson/dp/0471175412},
  year = 2000
}

@book{diestel2006graphentheorie,
  author = {Diestel, Reinhard},
  edition = {3 (electronic edition)},
  interhash = {f2579f4c24fdf2233f0a0565b34e8ac1},
  intrahash = {bf75f61d316d1d149e2b7e0d72cd937c},
  pages = {I-XVI, 1-344},
  publisher = {Springer-Verlag Heidelberg, New York},
  title = {Graph Theory},
  url = {http://www.math.ubc.ca/~solymosi/2007/443/GraphTheoryIII.pdf},
  year = 2005
}

@article{jrg1998densitybased,
  abstract = {The clustering algorithm DBSCAN relies on a density-based notion of clusters and is designed to discover clusters of arbitrary shape as well as to distinguish noise. In this paper, we generalize this algorithm in two important directions. The generalized algorithm—called GDBSCAN—can cluster point objects as well as spatially extended objects according to both, their spatial and their nonspatial attributes. In addition, four applications using 2D points (astronomy), 3D points (biology), 5D points (earth science) and 2D polygons (geography) are presented, demonstrating the applicability of GDBSCAN to real-world problems.
ER  -},
  author = {Sander, Jörg and Ester, Martin and Kriegel, Hans-Peter and Xu, Xiaowei},
  interhash = {3f2615cbf7c60d63f0a1ccc82e0caea1},
  intrahash = {a15f4445f49f37f272b373c69231a590},
  journal = {Data Mining and Knowledge Discovery},
  month = {#jun#},
  number = 2,
  pages = {169--194},
  title = {Density-Based Clustering in Spatial Databases: The Algorithm GDBSCAN and Its Applications},
  url = {http://dx.doi.org/10.1023/A:1009745219419},
  volume = 2,
  year = 1998
}

@inproceedings{Ester1996,
  author = {Ester, Martin and Kriegel, Hans-Peter and Sander, J{\"o}rg and Xu, Xiaowei},
  booktitle = {Proc. of 2nd International Conference on Knowledge Discovery and  Data Mining (KDD-96)},
  file = {:KDD96-037.pdf:PDF},
  interhash = {ba33e4d6b4e5b26bd9f543f26b7d250a},
  intrahash = {2f9e50f0a003c4d3067cab2b6fa47fe0},
  pages = {226-231},
  title = {A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise},
  year = 1996
}

@inproceedings{FalBarSpi07,
  author = {Falkowski, Tanja and Barth, Anja and Spiliopoulou, Myra},
  booktitle = {In Proc. of the 2007 IEEE / WIC / ACM International Conference on Web Intelligence,},
  interhash = {abd9653fc405547fd263c72c5bc5ae88},
  intrahash = {c0f9b82222d0c9a0b1cb0a5fa41a735a},
  pages = {112-115},
  title = {DENGRAPH: A Density-based Community Detection Algorithm},
  url = {http://wwwiti.cs.uni-magdeburg.de/~tfalkows/publ/2007/WI_FalBarSpi07.pdf},
  year = 2007
}

@inproceedings{ester1996,
  author = {Ester, M. and Kriegel, H. P. and Sander, J. and Xu, X.},
  booktitle = {Proc. 2 nd Int. Conf. on Knowledge Discovery and Data Mining(KDD ' 96)},
  date = {1996},
  interhash = {ba33e4d6b4e5b26bd9f543f26b7d250a},
  intrahash = {c1f11021ab9c80d7eb93321b0ef7decb},
  location = {Portland, OR},
  pages = {226-231},
  title = {A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise},
  year = 1996
}

@inproceedings{optics99,
  address = {Philadelphia, PA},
  author = {Ankerst, M. and Breunig, M. M. and Kriegel, H.-P. and Sander, J.},
  booktitle = {Proc. ACM SIGMOD Int. Conf. on Management of Data (SIGMOD'99)},
  interhash = {7417e17c0e8eec9f1a9f2bc57a476b15},
  intrahash = {40edf69f7de1e58c1480f7719e588c3d},
  pages = {49-60},
  title = {OPTICS: Ordering Points To Identify the Clustering Structure},
  year = 1999
}

@inproceedings{esterdbscan98,
  author = {Ester, Martin and Kriegel, Hans-Peter and Sander, Jörg and Xu, Xiaowei},
  booktitle = {Proceedings of the Second International Conference on Knowledge Discovery and Data Mining (KDD-96)},
  editor = {Simoudis, Evangelos and Han, Jiawei and Fayyad, Usama M.},
  interhash = {ba33e4d6b4e5b26bd9f543f26b7d250a},
  intrahash = {af881d23fe77ea9c365abe72f4c85d84},
  pages = {226-231},
  publisher = {AAAI Press},
  title = {A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise},
  year = 1996
}