@article{cimiano2006ontologies,
  abstract = {Ontologies are nowadays used for many applications requiring data, services and resources in general to be interoperable and machine understandable. Such applications are for example web service discovery and composition, information integration across databases, intelligent search, etc. The general idea is that data and services are semantically described with respect to ontologies,which are formal specifications of a domain of interest, and can thus be shared and reused in a way such that the shared meaning specified by the ontology remains formally the same across different parties and applications. As the cost of creating ontologies is relatively high, different proposals have emerged for learning ontologies from structured and unstructured resources. In this article we examine the maturity of techniques for ontology learning from textual resources, addressing the question whether the state-of-the-art is mature enough to produce ontologies ‘on demand’.},
  author = {Cimiano, Philipp and Völker, Johanna and Studer, Rudi},
  file = {cimiano2006ontologies.pdf:cimiano2006ontologies.pdf:PDF},
  groups = {public},
  interhash = {aeb553dc2e190f0a5974dfdc709d450a},
  intrahash = {fe4c2950b5be221b493e29e4339240e8},
  journal = {Information, Wissenschaft und Praxis},
  journalpub = {1},
  month = OCT,
  note = {see the special issue for more contributions related to the Semantic Web},
  number = {6-7},
  pages = {315-320},
  timestamp = {2008-07-23 11:47:29},
  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}},
  username = {dbenz},
  volume = 57,
  year = 2006
}

@incollection{rudolph2007supporting,
  abstract = {Designing and refining ontologies becomes a tedious task, once the boundary to real-world-size knowledge bases has been crossed. Hence semi-automatic methods supporting those tasks will determine the future success of ontologies in practice. In this paper we describe a way for ontology creation and refinement by combining techniques from natural language processing (NLP) and formal concept analysis (FCA). We point out how synergy between those two fields can be established thereby overcoming each other’s shortcomings.},
  address = {Berlin / Heidelberg},
  affiliation = {Institute AIFB, Universität Karlsruhe Germany},
  author = {Rudolph, Sebastian and Völker, Johanna and Hitzler, Pascal},
  booktitle = {Conceptual Structures: Knowledge Architectures for Smart Applications},
  doi = {10.1007/978-3-540-73681-3_41},
  editor = {Priss, Uta and Polovina, Simon and Hill, Richard},
  file = {rudolph2007supporting.pdf:rudolph2007supporting.pdf:PDF},
  groups = {public},
  interhash = {95939c2e69ef57fcf65e93df6010fe60},
  intrahash = {582e9add98a452d5cc6d4d0788d6e6d9},
  pages = {488-491},
  publisher = {Springer},
  series = {Lecture Notes in Computer Science},
  timestamp = {2010-11-10 11:28:57},
  title = {Supporting Lexical Ontology Learning by Relational Exploration},
  url = {http://dx.doi.org/10.1007/978-3-540-73681-3_41},
  username = {dbenz},
  volume = 4604,
  year = 2007
}