@article{Alonso2009273,
  author = {Alonso, S. and Cabrerizo, F.J. and Herrera-Viedma, E. and Herrera, F.},
  doi = {http://dx.doi.org/10.1016/j.joi.2009.04.001},
  interhash = {cbf95718465346edecef397149e4cf51},
  intrahash = {859c208f329fa96e26e35f1bcb7ab65d},
  issn = {1751-1577},
  journal = {Journal of Informetrics },
  number = 4,
  pages = {273 - 289},
  title = {h-Index: A review focused in its variants, computation and standardization for different scientific fields },
  url = {http://www.sciencedirect.com/science/article/pii/S1751157709000339},
  volume = 3,
  year = 2009
}

@misc{goldenberg2009survey,
  abstract = {Networks are ubiquitous in science and have become a focal point for
discussion in everyday life. Formal statistical models for the analysis of
network data have emerged as a major topic of interest in diverse areas of
study, and most of these involve a form of graphical representation.
Probability models on graphs date back to 1959. Along with empirical studies in
social psychology and sociology from the 1960s, these early works generated an
active network community and a substantial literature in the 1970s. This effort
moved into the statistical literature in the late 1970s and 1980s, and the past
decade has seen a burgeoning network literature in statistical physics and
computer science. The growth of the World Wide Web and the emergence of online
networking communities such as Facebook, MySpace, and LinkedIn, and a host of
more specialized professional network communities has intensified interest in
the study of networks and network data. Our goal in this review is to provide
the reader with an entry point to this burgeoning literature. We begin with an
overview of the historical development of statistical network modeling and then
we introduce a number of examples that have been studied in the network
literature. Our subsequent discussion focuses on a number of prominent static
and dynamic network models and their interconnections. We emphasize formal
model descriptions, and pay special attention to the interpretation of
parameters and their estimation. We end with a description of some open
problems and challenges for machine learning and statistics.},
  author = {Goldenberg, Anna and Zheng, Alice X and Fienberg, Stephen E and Airoldi, Edoardo M},
  interhash = {bab22de06306d84cf357aadf48982d87},
  intrahash = {5e341981218d7cd89416c3371d56c794},
  note = {cite arxiv:0912.5410Comment: 96 pages, 14 figures, 333 references},
  title = {A survey of statistical network models},
  url = {http://arxiv.org/abs/0912.5410},
  year = 2009
}

@article{Lü20121,
  abstract = {The ongoing rapid expansion of the Internet greatly increases the necessity of effective recommender systems for filtering the abundant information. Extensive research for recommender systems is conducted by a broad range of communities including social and computer scientists, physicists, and interdisciplinary researchers. Despite substantial theoretical and practical achievements, unification and comparison of different approaches are lacking, which impedes further advances. In this article, we review recent developments in recommender systems and discuss the major challenges. We compare and evaluate available algorithms and examine their roles in the future developments. In addition to algorithms, physical aspects are described to illustrate macroscopic behavior of recommender systems. Potential impacts and future directions are discussed. We emphasize that recommendation has great scientific depth and combines diverse research fields which makes it interesting for physicists as well as interdisciplinary researchers.},
  author = {Lü, Linyuan and Medo, Matúš and Yeung, Chi Ho and Zhang, Yi-Cheng and Zhang, Zi-Ke and Zhou, Tao},
  doi = {10.1016/j.physrep.2012.02.006},
  interhash = {408fbf13302368693d501271268cda03},
  intrahash = {9594d6b87d49d22b783b9c95da1f59af},
  issn = {0370-1573},
  journal = {Physics Reports},
  note = {Recommender Systems},
  number = 1,
  pages = {1 - 49},
  title = {Recommender systems},
  url = {http://www.sciencedirect.com/science/article/pii/S0370157312000828},
  volume = 519,
  year = 2012
}

@article{journals/siamrev/KoldaB09,
  author = {Kolda, Tamara G. and Bader, Brett W.},
  ee = {http://dx.doi.org/10.1137/07070111X},
  interhash = {b30bb2d42e1a05fc41370c50844822ad},
  intrahash = {6b115affb18f3f1f99411596c03787f8},
  journal = {SIAM Review},
  number = 3,
  pages = {455-500},
  title = {Tensor Decompositions and Applications.},
  url = {http://dblp.uni-trier.de/db/journals/siamrev/siamrev51.html#KoldaB09},
  volume = 51,
  year = 2009
}

@article{journals/corr/abs-1103-0398,
  author = {Collobert, Ronan and Weston, Jason and Bottou, Léon and Karlen, Michael and Kavukcuoglu, Koray and Kuksa, Pavel P.},
  ee = {http://arxiv.org/abs/1103.0398},
  interhash = {c1e968fc1903e842ab3c638cd5ffca61},
  intrahash = {24c6f6531a70625136167307bc15a480},
  journal = {CoRR},
  note = {informal publication},
  title = {Natural Language Processing (almost) from Scratch},
  url = {http://static.googleusercontent.com/external_content/untrusted_dlcp/research.google.com/de//pubs/archive/35671.pdf},
  volume = {abs/1103.0398},
  year = 2011
}

@proceedings{Gunawardana2935,
  author = {Gunawardana, Asela and Shani, Guy},
  interhash = {441df9b673faf85aecc45babd8883069},
  intrahash = {49600df05a884106989d71dedcaa7e1b},
  page = {2935−2962},
  series = 2935,
  title = { A Survey of Accuracy Evaluation Metrics of Recommendation Tasks },
  url = {http://jmlr.csail.mit.edu/papers/v10/gunawardana09a.html},
  volume = {v10},
  year = 2009
}

@proceedings{30474,
  author = {Tresp, Volker and Bundschus, Markus and Rettinger, Achim and Huang, Yi},
  interhash = {e27fbf5b5fb16f66cd0c7a3932fc4695},
  intrahash = {006468688804bc3563225b8dcd7aea97},
  journal = {Uncertainty Reasoning for the Semantic Web I Lecture Notes in AI},
  publisher = {Springer},
  title = {Towards machine learning on the semantic web},
  url = {http://wwwbrauer.informatik.tu-muenchen.de/~trespvol/papers/LearningRDF23.pdf},
  year = 2008
}

@article{4686305,
  abstract = {Social tagging systems have recently became very popular as a means to classify large sets of resources shared among on-line communities over the social Web. However, the folksonomies resulting from the use of these systems revealed limitations : tags are ambiguous and their spelling may vary, and folksonomies are difficult to exploit in order to retrieve or exchange information. This article compares the recent attempts to overcome these limitations and to support the use of folksonomies with formal languages and ontologies from the Semantic Web.},
  author = {Limpens, Freddy and Gandon, Fabien and Buffa, Michel},
  doi = {10.1109/ASEW.2008.4686305},
  interhash = {cb1d534be80d664a50df66e8977b774e},
  intrahash = {9372f9c2db8b9f4cf05b3db84e6589ac},
  journal = {Automated Software Engineering - Workshops, 2008. ASE Workshops 2008. 23rd IEEE/ACM International Conference on},
  month = {Sept.},
  pages = {13-18},
  title = {Bridging ontologies and folksonomies to leverage knowledge sharing on the social Web: A brief survey},
  year = 2008
}

@article{1282,
  author = {Cimiano, Philipp and Völker, Johanna and Studer, Rudi},
  interhash = {aeb553dc2e190f0a5974dfdc709d450a},
  intrahash = {fe4c2950b5be221b493e29e4339240e8},
  journal = {Information, Wissenschaft und Praxis},
  month = OCT,
  note = {see the special issue for more contributions related to the Semantic Web},
  number = {6-7},
  pages = {315-320},
  title = {Ontologies on Demand? - A Description of the State-of-the-Art, Applications, Challenges and Trends for Ontology Learning from Text},
  url = {\url{http://www.aifb.uni-karlsruhe.de/WBS/pci/Publications/iwp06.pdf}},
  volume = 57,
  year = 2006
}

@misc{voss-2007,
  abstract = {This paper gives an overview of current trends in manual indexing on the Web. Along with a general rise of user generated content there are more and more tagging systems that allow users to annotate digital resources with tags (keywords) and share their annotations with other users. Tagging is frequently seen in contrast to traditional knowledge organization systems or as something completely new. This paper shows that tagging should better be seen as a popular form of manual indexing on the Web. Difference between controlled and free indexing blurs with sufficient feedback mechanisms. A revised typology of tagging systems is presented that includes different user roles and knowledge organization systems with hierarchical relationships and vocabulary control. A detailed bibliography of current research in collaborative tagging is included.},
  author = {Voss, Jakob},
  interhash = {c293cd6ef590c6aaf32df75cbdb9de82},
  intrahash = {9ec98351dc630ea6b1f65046ba44a8dd},
  title = {Tagging, Folksonomy \& Co - Renaissance of Manual Indexing?},
  url = {http://www.citebase.org/abstract?id=oai:arXiv.org:cs/0701072},
  year = 2007
}

@article{Rui05SurveyClustering,
  abstract = {Data analysis plays an indispensable role for understanding various
	phenomena. Cluster analysis, primitive exploration with little or
	no prior knowledge, consists of research developed across a wide
	variety of communities. The diversity, on one hand, equips us with
	many tools. On the other hand, the profusion of options causes confusion.
	We survey clustering algorithms for data sets appearing in statistics,
	computer science, and machine learning, and illustrate their applications
	in some benchmark data sets, the traveling salesman problem, and
	bioinformatics, a new field attracting intensive efforts. Several
	tightly related topics, proximity measure, and cluster validation,
	are also discussed.},
  author = {Xu, Rui and Wunsch, II},
  interhash = {7bd8c3f3c7ea707f110d76123e0d097c},
  intrahash = {92c03ba02a41f95ae315273939c8daa5},
  issn = {1045-9227},
  journal = {Neural Networks, IEEE Transactions on},
  number = 3,
  owner = {mgrani},
  pages = {645--678},
  timestamp = {2006.06.08},
  title = {Survey of clustering algorithms},
  volume = 16,
  year = 2005
}