@article{McRae:2005:Behav-Res-Methods:16629288,
  abstract = {Semantic features have provided insight into numerous behavioral phenomena concerning concepts, categorization, and semantic memory in adults, children, and neuropsychological populations. Numerous theories and models in these areas are based on representations and computations involving semantic features. Consequently, empirically derived semantic feature production norms have played, and continue to play, a highly useful role in these domains. This article describes a set of feature norms collected from approximately 725 participants for 541 living (dog) and nonliving (chair) basic-level concepts, the largest such set of norms developed to date. This article describes the norms and numerous statistics associated with them. Our aim is to make these norms available to facilitate other research, while obviating the need to repeat the labor-intensive methods involved in collecting and analyzing such norms. The full set of norms may be downloaded from www.psychonomic.org/archive.},
  author = {McRae, K and Cree, G S and Seidenberg, M S and McNorgan, C},
  interhash = {209f2874b49fd74fce1fe0ad645733e2},
  intrahash = {936af12b025e37b0a6aac6bc103f58a3},
  journal = {Behav Res Methods},
  month = Nov,
  number = 4,
  pages = {547-559},
  pmid = {16629288},
  title = {Semantic feature production norms for a large set of living and nonliving things},
  url = {http://www.ncbi.nlm.nih.gov/pubmed/16629288},
  volume = 37,
  year = 2005
}

@misc{narayanan-2006,
  abstract = { We present a new class of statistical de-anonymization attacks against high-dimensional micro-data, such as individual preferences, recommendations, transaction records and so on. Our techniques are robust to perturbation in the data and tolerate some mistakes in the adversary's background knowledge.},
  author = {Narayanan, Arvind and Shmatikov, Vitaly},
  interhash = {6be42821c2588b6442d6fb8ac7cd8a6e},
  intrahash = {86b686a7fad55fa225123b2f79de87a8},
  title = {How To Break Anonymity of the Netflix Prize Dataset},
  url = {http://www.citebase.org/abstract?id=oai:arXiv.org:cs/0610105},
  year = 2006
}

@misc{Newman+Hettich+Blake+Merz:1998,
  author = {Newman, C.L. Blake D.J. and Merz, C.J.},
  institution = {University of California, Irvine, Dept. of Information and Computer Sciences},
  interhash = {325a6b5ac5a1f044943d4298c21d31dd},
  intrahash = {85308db3df761f63f16a7cab4eb8d4aa},
  title = {{UCI} Repository of machine learning databases},
  url = {http://www.ics.uci.edu/$\sim$mlearn/MLRepository.html},
  year = 1998
}