@inproceedings{omelayenko2001learning,
  abstract = {The next generation of the Web, called Semantic Web, has to improve the Web with semantic (ontological) page annotations to enable knowledge-level querying and searches. Manual construction of these ontologies will require tremendous efforts that force future integration of machine learning with knowledge acquisition to enable highly automated ontology learning. In the paper we present the state of the-art in the field of ontology learning from the Web to see how it can contribute to the task of semantic Web querying. We consider three components of the query processing system: natural language ontologies, domain ontologies and ontology instances. We discuss the requirements for machine learning algorithms to be applied for the learning of the ontologies of each type from the Web documents, and survey the existent ontology learning and other closely related approaches.},
  author = {Omelayenko, Borys},
  booktitle = {Proceedings of the International Workshop on Web Dynamics, held in conj. with the 8th International Conference on Database Theory (ICDT’01), London, UK},
  file = {omelayenko2001learning.pdf:omelayenko2001learning.pdf:PDF},
  groups = {public},
  interhash = {011d45b904b02fdf1a65122d2832710b},
  intrahash = {3edf80da8b39eefeea46379581628adf},
  timestamp = {2011-02-02 15:03:05},
  title = {Learning of Ontologies for the Web: the Analysis of Existent Approaches},
  url = {http://www.dcs.bbk.ac.uk/webDyn/webDynPapers/omelayenko.pdf},
  username = {dbenz},
  year = 2001
}

@inproceedings{damme2007folksontology,
  abstract = {We can observe that the amount of non-toy domain ontologies is stillvery limited for many areas of interest. In contrast, folksonomies are widely inuse for (1) tagging Web pages (e.g. del.icio.us), (2) annotating pictures (e.g.flickr), or (3) classifying scholarly publications (e.g. bibsonomy). However,such folksonomies cannot offer the expressivity of ontologies, and therespective tags often lack a context-independent and intersubjective definitionof meaning. Also, folksonomies and other unsupervised vocabularies frequentlysuffer from inconsistencies and redundancies. In this paper, we argue that thesocial interaction manifested in folksonomies and in their usage should beexploited for building and maintaining ontologies. Then, we sketch acomprehensive approach for deriving ontologies from folksonomies byintegrating multiple resources and techniques. In detail, we suggest combining(1) the statistical analysis of folksonomies, associated usage data, and theirimplicit social networks, (2) online lexical resources like dictionaries, Wordnet,Google and Wikipedia, (3) ontologies and Semantic Web resources, (4)ontology mapping and matching approaches, and (5) functionality that helpshuman actors in achieving and maintaining consensus over ontology elementsuggestions resulting from the preceding steps.},
  author = {Damme, Céline Van and Hepp, Martin and Siorpaes, Katharina},
  booktitle = {Bridging the Gep between Semantic Web and Web 2.0 (SemNet 2007)},
  file = {damme2007folksontology.pdf:damme2007folksontology.pdf:PDF},
  groups = {public},
  interhash = {c8d1bcaa606229417f1c3f0f27c5f0e0},
  intrahash = {ace5ff38dde26e6c9dbf9db4e31e6546},
  pages = {57-70},
  timestamp = {2011-02-02 15:25:23},
  title = {FolksOntology: An Integrated Approach for Turning Folksonomies into Ontologies},
  url = {http://www.kde.cs.uni-kassel.de/ws/eswc2007/proc/FolksOntology.pdf},
  username = {dbenz},
  year = 2007
}