@inproceedings{suchanek2007semantic,
  abstract = {We present YAGO, a light-weight and extensible ontology with high coverage and quality. YAGO builds on entities and relations and currently contains more than 1 million entities and 5 million facts. This includes the Is-A hierarchy as well as non-taxonomic relations between entities (such as HASONEPRIZE). The facts have been automatically extracted from Wikipedia and unified with WordNet, using a carefully designed combination of rule-based and heuristic methods described in this paper. The resulting knowledge base is a major step beyond WordNet: in <i>quality</i> by adding knowledge about individuals like persons, organizations, products, etc. with their semantic relationships - and in <i>quantity</i> by increasing the number of facts by more than an order of magnitude. Our empirical evaluation of fact correctness shows an accuracy of about 95%. YAGO is based on a logically clean model, which is decidable, extensible, and compatible with RDFS. Finally, we show how YAGO can be further extended by state-of-the-art information extraction techniques.},
  acmid = {1242667},
  address = {New York, NY, USA},
  author = {Suchanek, Fabian M. and Kasneci, Gjergji and Weikum, Gerhard},
  booktitle = {Proceedings of the 16th international conference on World Wide Web},
  doi = {10.1145/1242572.1242667},
  interhash = {1d2c2b23ce2a6754d12c4364e19c574c},
  intrahash = {84ae693c0a6dfb6d4b051b0b6dbd3668},
  isbn = {978-1-59593-654-7},
  location = {Banff, Alberta, Canada},
  numpages = {10},
  pages = {697--706},
  publisher = {ACM},
  title = {YAGO: a core of semantic knowledge},
  url = {http://doi.acm.org/10.1145/1242572.1242667},
  year = 2007
}

@article{davis1993knowledge,
  abstract = {Although knowledge representation is one of the central and in some ways most familiar concepts in AI, the most fundamental question about it--What is it?--has rarely been answered directly. Numerous papers have lobbied for one or another variety of representation, other papers have argued for various properties a representation should have, while still others have focused on properties that are important to the notion of representation in general.

In this paper we go back to basics to address the question directly. We believe that the answer can best be understood in terms of five important and distinctly different roles that a representation plays, each of which places different and at times conflicting demands on the properties a representation should have.

We argue that keeping in mind all five of these roles provides a usefully broad perspective that sheds light on some longstanding disputes and can invigorate both research and practice in the field. },
  author = {Davis, Randall and Shrobe, Howard and Szolovits, Peter},
  interhash = {0a9d5e8f1265106c18730053f871e80b},
  intrahash = {fc0910c9b3d967f5b01ae73d252d66fb},
  journal = {AI Magazine},
  number = 1,
  pages = {17--33},
  title = {What is a Knowledge Representation},
  url = {http://www.aaai.org/aitopics/assets/PDF/AIMag14-01-002.pdf},
  volume = 14,
  year = 1993
}

@inbook{schmitz2006kollaboratives,
  abstract = {Wissensmanagement in zentralisierten Wissensbasen erfordert
einen hohen Aufwand für Erstellung und Wartung, und es entspricht nicht
immer den Anforderungen der Benutzer. Wir geben in diesem Kapitel einen Überblick
über zwei aktuelle Ansätze, die durch kollaboratives Wissensmanagement
diese Probleme lösen können. Im Peer-to-Peer-Wissensmanagement unterhalten
Benutzer dezentrale Wissensbasen, die dann vernetzt werden können, um
andere Benutzer eigene Inhalte nutzen zu lassen. Folksonomies versprechen, die
Wissensakquisition so einfach wie möglich zu gestalten und so viele Benutzer in
den Aufbau und die Pflege einer gemeinsamen Wissensbasis einzubeziehen.},
  author = {Schmitz, Christoph and Hotho, Andreas and Jäschke, Robert and Stumme, Gerd},
  booktitle = {Semantic Web - Wege zur vernetzten Wissensgesellschaft},
  editor = {Pellegrini, Tassilo and Blumauer, Andreas},
  interhash = {cc0f3d4fa8f36968f02837e3f9f5c57b},
  intrahash = {53e13744981f2c04d9239e0cf9b4e689},
  isbn = {3-540-29324-8},
  pages = {273-290},
  publisher = {Springer},
  title = {Kollaboratives Wissensmanagement},
  url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/hotho2006kollaboratives.pdf},
  year = 2006
}

@inproceedings{Lange:2006:ASW4MKM,
  author = {Lange, Christoph and Kohlhase, Michael},
  booktitle = {Proceedings of the First Workshop on Semantic Wikis -- From Wiki
	To Semantics},
  crossref = {SemWiki2006-proceedings},
  editor = {V\"{o}lkel, Max and Schaffert, Sebastian},
  interhash = {52fb2651a1376b7c11c0375ed91658f9},
  intrahash = {09499c09e4c9b63f2d881ecdf13795bf},
  month = {June},
  owner = {voelkel},
  publisher = {ESWC2006},
  series = {Workshop on Semantic Wikis},
  timestamp = {2006.06.14},
  title = {A Semantic Wiki for Mathematical Knowledge Management},
  url = {http://semwiki.org/semwiki2006},
  year = 2006
}