@inproceedings{linguistically2009,
  abstract = {In this paper we argue why it is necessary to associate linguistic information with ontologies and why more expressive models, beyond RDFS, OWL and SKOS, are needed to capture the relation between natural language constructs on the one hand and ontological entities on the other. We argue that in the light of tasks such as ontology-based information extraction, ontology learning and population from text and natural language generation from ontologies, currently available datamodels are not sufficient as they only allow to associate atomic terms without linguistic grounding or structure to ontology elements. Towards realizing a more expressive model for associating linguistic information to ontology elements, we base our work presented here on previously developed models (LingInfo, LexOnto, LMF) and present a new joint model for linguistic grounding of ontologies called LexInfo. LexInfo combines essential design aspects of LingInfo and LexOnto and builds on a sound model for representing computational lexica called LMF which has been recently approved as a standard under ISO.},
  author = {Buitelaar, Paul and Cimiano, Philipp and Haase, Peter and Sintek, Michael},
  booktitle = {6th Annual European Semantic Web Conference (ESWC2009)},
  interhash = {28225358e49213819fa071deb62c4aa1},
  intrahash = {8213d4d08414fd60fe86e59d41895d4e},
  month = {June},
  pages = {111-125},
  title = {Towards Linguistically Grounded Ontologies},
  url = {http://www.cimiano.de/Publications/2009/eswc09/eswc09.pdf},
  year = 2009
}

@inproceedings{nldb05,
  address = {Alicante, Spain},
  author = {Cimiano, Philipp and Völker, Johanna},
  booktitle = {Proceedings of the 10th International Conference on Applications of Natural Language to Information Systems (NLDB)},
  editor = {Montoyo, Andres and Munoz, Rafael and Metais, Elisabeth},
  interhash = {c90cb094c9f4f3cca1214d0478ffeb07},
  intrahash = {072436e5adc4f5fdc39f4baeaa55b077},
  month = JUN,
  pages = {227-238},
  publisher = {Springer},
  series = {Lecture Notes in Computer Science},
  title = {Text2Onto - A Framework for Ontology Learning and Data-driven Change Discovery},
  url = {\url{http://www.aifb.uni-karlsruhe.de/WBS/jvo/publications/Text2Onto_nldb_2005.pdf}},
  volume = 3513,
  year = 2005
}

@inproceedings{tane06query,
  author = {Tane, Julien and Cimiano, Philipp and Hitzler, Pascal},
  bibsource = {DBLP, http://dblp.uni-trier.de},
  booktitle = {Proc. 14th Intl. Conf. on Conceptual Structures},
  crossref = {DBLP:conf/iccs/2006},
  editor = {Sch{\"a}rfe, Henrik and Hitzler, Pascal and {\O}hrstr{\o}m, Peter},
  ee = {http://dx.doi.org/10.1007/11787181_30},
  interhash = {dd81fbdd68945575807f3b42558d6a8a},
  intrahash = {7dc1c278a8b3202c10349bd823f5c98b},
  isbn = {3-540-35893-5},
  pages = {413-426},
  publisher = {Springer},
  series = {LNCS},
  title = {Query-Based Multicontexts for Knowledge Base Browsing: An Evaluation.},
  volume = 4068,
  year = 2006
}

@book{buitelaar2008ontology,
  asin = {1586038184},
  author = {Buitelaar, Paul and Cimiano, Philipp},
  dewey = {006.33},
  ean = {9781586038182},
  edition = {illustrated edition},
  interhash = {985072a36f1f789052de6678e17e4eb8},
  intrahash = {c7267178358f790c16aac7288ad56167},
  isbn = {1586038184},
  publisher = {Ios Press Inc},
  title = {Ontology Learning and Population: Bridging the Gap Between Text and Knowledge },
  url = {http://www.booksonline.iospress.nl/Content/View.aspx?piid=8211},
  volume = 167,
  year = 2008
}

@book{cimiano2006ontology,
  author = {Cimiano, Philipp},
  ee = {http://dx.doi.org/10.1007/978-0-387-39252-3},
  interhash = {f8a70c22cfd162dc9ad2cd977d79b66c},
  intrahash = {09ab696de72e68b0b2aaf21ae3b0b613},
  isbn = {978-0-387-30632-2},
  pages = {I-XXVIII, 1-347},
  publisher = {Springer},
  title = {Ontology learning and population from text - algorithms, evaluation and applications.},
  year = 2006
}

@incollection{cimiano2009ontology,
  affiliation = {University of Karlsruhe Institute AIFB Karlsruhe Germany},
  author = {Cimiano, Philipp and M{\"{a}}dche, Alexander and Staab, Steffen and V{\"{o}}lker, Johanna},
  booktitle = {Handbook on Ontologies},
  editor = {Staab, Steffen and Studer, Rudi},
  interhash = {884c5b59450bf7982a4345f523181404},
  intrahash = {3081beee709710cd12ca402a00526ef2},
  isbn = {978-3-540-92673-3},
  keyword = {Economics/Management Science},
  pages = {245-267},
  publisher = {Springer Berlin Heidelberg},
  series = {International Handbooks Information System},
  title = {Ontology Learning},
  url = {http://dx.doi.org/10.1007/978-3-540-92673-3_11},
  year = 2009
}

@article{ieKey,
  author = {Cimiano, Philipp and V"olker, Johanna and Studer, Rudi},
  date = {October 2006},
  interhash = {0007185516cf6c93931a11bc13c55f3f},
  intrahash = {bd70c98a41d8cc01464dd022dfd118b6},
  journal = {Information, Wissenschaft und Praxis},
  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 Information},
  url = {http://www.aifb.uni-karlsruhe.de/Publikationen/showPublikation?publ_id=1282},
  volume = 57,
  year = 2006
}

@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
}

@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
}

@incollection{bloehdorn2006learning,
  abstract = {Recent work has shown improvements in text clustering and classification tasks by integrating conceptual features extracted from ontologies. In this paper we present text mining experiments in the medical domain in which the ontological structures used are acquired automatically in an unsupervised learning process from the text corpus in question. We compare results obtained using the automatically learned ontologies with those obtained using manually engineered ones. Our results show that both types of ontologies improve results on text clustering and classification tasks, whereby the automatically acquired ontologies yield a improvement competitive with the manually engineered ones.
ER  -},
  author = {Bloehdorn, Stephan and Cimiano, Philipp and Hotho, Andreas},
  booktitle = {From Data and Information Analysis to Knowledge Engineering},
  doi = {http://dx.doi.org/10.1007/3-540-31314-1_40},
  interhash = {cf1af505b638677f00b3d3d7a5903199},
  intrahash = {bc1d40cf4fd64780ecf712b1e40f31de},
  isbn = {978-3-540-31313-7},
  pages = {334--341},
  publisher = {Springer Berlin Heidelberg},
  title = {Learning Ontologies to Improve Text Clustering and Classification},
  url = {http://www.kde.cs.uni-kassel.de/hotho/pub/2006/2006-03-gfkl05-bloehdorn-etal-learning-ontologies.pdf},
  year = 2006
}

@article{cimiano05learning,
  author = {Cimiano, Philipp and Hotho, Andreas and Staab, Steffen},
  ee = {http://www.jair.org/papers/paper1648.html},
  interhash = {4c09568cff62babd362aab03095f4589},
  intrahash = {eaaf0e4b3a8b29fab23b6c15ce2d308d},
  journal = {Journal on Artificial Intelligence Research},
  pages = {305-339},
  title = {Learning Concept Hierarchies from Text Corpora using Formal Concept Analysis},
  url = {http://dblp.uni-trier.de/db/journals/jair/jair24.html#CimianoHS05},
  volume = 24,
  year = 2005
}

@techreport{cimianpo_hotho_staab_OL_FCA_04,
  author = {Cimiano, Philipp and Hotho, Andreas and Staab, Steffen},
  institution = {Institute AIFB, Universität Karlsruhe},
  interhash = {f558a89c579eba3ae4ef04854ca2efb6},
  intrahash = {c46361a68b3dd167a288ba05a74a88bb},
  month = NOV,
  title = {Learning Concept Hierarchies from Text Corpora using Formal Concept Analysis},
  url = {http://www.kde.cs.uni-kassel.de/hotho/pub/2004/techOntologylearningFCA.pdf},
  year = 2004
}

@inproceedings{sorg2008cirwesa,
  author = {Sorg, Philipp and Cimiano, Philipp},
  booktitle = {Working  Notes for the CLEF 2008 Workshop},
  evastar_pdf = {2008_1837_Sorg_Cross-lingual_I_1.pdf},
  interhash = {7063c5bdff3528939877aa07ae4a35de},
  intrahash = {27c1c374a750725824118ac02ba5f2c6},
  title = {Cross-lingual Information Retrieval with Explicit Semantic Analysis},
  type = {Inproceedings},
  url = {http://www.aifb.kit.edu/images/7/7c/2008_1837_Sorg_Cross-lingual_I_1.pdf},
  year = 2008
}

@inproceedings{cimiano2004concept,
  address = {Heidelberg},
  author = {Cimiano, Philipp and Hotho, Andreas and Stumme, Gerd and Tane, Julien},
  booktitle = {Concept Lattices},
  editor = {Eklund, Peter},
  interhash = {e42d9895b0d816f231227f1be15b03dc},
  intrahash = {062d956cd265215f53fdc7b8401b7f15},
  isbn = {3-540-23258-3},
  organization = {Second International Conference on Formal Concept Analysis, ICFCA 2004},
  pages = {189-207},
  publisher = {Springer},
  series = {LNAI},
  title = {Conceptual Knowledge Processing with Formal Concept Analysis and Ontologies},
  url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2004/cimiano2004concept.pdf},
  volume = 2961,
  year = 2004
}

@inproceedings{cimiano2004concept,
  abstract = {Among many other knowledge representations formalisms, Ontologies
and Formal Concept Analysis (FCA) aim at modeling 'concepts'. We
discuss how these two formalisms may complement another from an
application point of view. In particular, we will see how FCA can
be used to support Ontology Engineering, and how ontologies can be
exploited in FCA applications. The interplay of FCA and ontologies
is studied along the life cycle of an ontology:
 (i) FCA can support the building of the ontology as a
 learning technique.
 (ii) The established ontology can be analyzed and navigated by
 using techniques of FCA.
 (iii) Last but not least, the ontology may be used to improve an FCA
 application.},
  address = {Heidelberg},
  author = {Cimiano, Philipp and Hotho, Andreas and Stumme, Gerd and Tane, Julien},
  booktitle = {Concept Lattices},
  editor = {Eklund, Peter},
  interhash = {e42d9895b0d816f231227f1be15b03dc},
  intrahash = {062d956cd265215f53fdc7b8401b7f15},
  isbn = {3-540-23258-3},
  organization = {Second International Conference on Formal Concept Analysis, ICFCA 2004},
  pages = {189-207},
  publisher = {Springer},
  series = {LNAI},
  title = {Conceptual Knowledge Processing with Formal Concept Analysis and Ontologies},
  url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2004/cimiano2004concept.pdf},
  volume = 2961,
  year = 2004
}

@incollection{cimiano2004conceptual,
  address = {Berlin/Heidelberg},
  author = {Cimiano, Philipp and Hotho, Andreas and Stumme, Gerd and Tane, Julien},
  booktitle = {Concept Lattices},
  editor = {Eklund, Peter},
  interhash = {e42d9895b0d816f231227f1be15b03dc},
  intrahash = {9676ee1ded2b73fa90253a2a5dccdbf8},
  isbn = {978-3-540-21043-6},
  pages = {189--207},
  publisher = {Springer},
  series = {Lecture Notes in Computer Science},
  title = {Conceptual Knowledge Processing with Formal Concept
                   Analysis and Ontologies},
  url = {http://dx.doi.org/10.1007/978-3-540-24651-0_18},
  volume = 2961,
  year = 2004
}

@inproceedings{cimiano2004comparing,
  abstract = {The application of clustering methods for automatic taxonomy construction from text requires knowledge about the tradeoff between, (i), their effectiveness (quality of result), (ii), efficiency (run-time behaviour), and, (iii), traceability of the taxonomy construction by the ontology engineer. In this line, we present an original conceptual clustering method based on Formal Concept Analysis for automatic taxonomy construction and compare it with hierarchical agglomerative clustering and hierarchical divisive clustering.},
  author = {Cimiano, Philipp and Hotho, Andreas and Staab, Steffen},
  booktitle = {ECAI 2004 Proceedings of the 16th European Conference on Artificial Intelligence, 22 - 27 August, Valencia, Spain},
  editor = {de M\'{a}ntaras, R. L\'{o}pez and Saitta, L.},
  file = {cimiano2004comparing.pdf:cimiano2004comparing.pdf:PDF},
  groups = {public},
  interhash = {5ebc73142f0c4d51a1037432435bab94},
  intrahash = {4e2f4ba3e051f120c2bc8216aad7cdaa},
  pages = {435-439},
  publisher = {IOS Press},
  timestamp = {2011-02-02 13:38:11},
  title = {Comparing Conceptual, Divise and Agglomerative Clustering for Learning Taxonomies from Text},
  username = {dbenz},
  year = 2004
}

@inproceedings{conf/birthday/BloehdornBCGHLMMSSV11,
  author = {Bloehdorn, Stephan and Blohm, Sebastian and Cimiano, Philipp and Giesbrecht, Eugenie and Hotho, Andreas and Lösch, Uta and Mädche, Alexander and Mönch, Eddie and Sorg, Philipp and Staab, Steffen and Völker, Johanna},
  booktitle = {Foundations for the Web of Information and Services},
  crossref = {conf/birthday/2011studer},
  editor = {Fensel, Dieter},
  ee = {http://dx.doi.org/10.1007/978-3-642-19797-0_7},
  interhash = {db48314326a36fc4ac8770cba2c20e49},
  intrahash = {21be5153a8f491c9f209d57ce7662387},
  isbn = {978-3-642-19796-3},
  pages = {115-142},
  publisher = {Springer},
  title = {Combining Data-Driven and Semantic Approaches for Text Mining.},
  url = {http://dblp.uni-trier.de/db/conf/birthday/studer2011.html#BloehdornBCGHLMMSSV11},
  year = 2011
}

@inproceedings{cimiano2003automaticb,
  author = {Cimiano, Philipp and Staab, Steffen and Tane, Julien},
  booktitle = {Proceedings of the ECML/PKDD Workshop on Adaptive Text Extraction and Mining, Cavtat-Dubrovnik, Croatia},
  interhash = {2f9df79fa0d890faa91dc1d0d0def735},
  intrahash = {c62b4e1dc65490d68bef7eaed01f83ea},
  lastdatemodified = {2007-03-22},
  lastname = {Cimiano},
  own = {notown},
  pages = {10-17},
  pdf = {cimiano03-automatic.pdf},
  read = {notread},
  title = {Automatic Acquisition of Taxonomies from Text: FCA meets NLP},
  url = {\url{http://www.aifb.uni-karlsruhe.de/WBS/pci/ontolearning.pdf}},
  year = 2003
}

@inproceedings{cimiano2003automatic,
  abstract = {We present a novel approach to the automatic acquisition of taxonomies or concept hierarchies from domain-specific texts based on Formal Concept Analysis (FCA). Our approach is based on the assumption that verbs pose more or less strong selectional restrictions on their arguments. The conceptual hierarchy is then built on the basis of the inclusion relations between the extensions of the selectional restrictions of all the verbs, while the verbs themselves provide intensional descriptions for each concept. We formalize this idea in terms of FCA and show how our approach can be used to acquire a concept hierarchy for the tourism domain out of texts. We then evaluate our method by considering an already existing ontology for this domain.},
  address = {Cavtat-Dubrovnik, Croatia},
  author = {Cimiano, Philipp and Staab, Steffen and Tane, Julien},
  booktitle = {Proceedings of the ECML / PKDD Workshop on Adaptive Text Extraction and Mining},
  file = {cimiano2003automatic.pdf:cimiano2003automatic.pdf:PDF},
  groups = {public},
  interhash = {2f9df79fa0d890faa91dc1d0d0def735},
  intrahash = {573ac0e71d6b1c369cf881ddda8c7841},
  pages = {10--17},
  pdf = {cimiano2003automatic.pdf},
  timestamp = {2008-07-07 15:50:15},
  title = {Automatic Acquisition of Taxonomies from Text: FCA meets NLP},
  url = {http://www.dcs.shef.ac.uk/~fabio/ATEM03/cimiano-ecml03-atem.pdf},
  username = {dbenz},
  year = 2003
}