Ontologies on demand? A description of the state-of-the-art, applications, challenges and trends for ontology learning from text

Information-Wissenschaft und Praxis

Volumn 57, Issue 6-7, 2006, Pages 315-320

  Cimiano, Philipp ^a   Völker, Johanna ^a   Studer, Rudi ^a  

^a NONE

Author keywords

Knowledge Representation; Machine Learning; Research; Semantic Web; State of the Art; Text Mining

Indexed keywords

EID: 33749657990     PISSN: 14344653     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Review

References (34)

1. [Agichtein & Gravano 2000] E. Agichtein and L. Gravano: Snowball: extracting relations from large plain-text collections. Proceedings of the ACM Conference on Digital Libraries, pp. 85-94, 2000.
2. [Baeza-Yates and Ribeiro-Neto 1999] R. Baeza-Yates, B. Ribeiro-Neto: Modern Information Retrieval. Addison Wesley, 1999.
3. [Berners-Lee et al. 2001] T. Berners-Lee, J. Hendler, O. Lassila: The Semantic Web. Scientific American 284(5), pp. 34-43, 2001.
4. [Bloehdorn et al. 2005] S. Bloehdorn, P. Cimiano, A. Hotho: Learning Ontologies to Improve Text Clustering and Classification. From Data and Information Analysis to Knowledge Engineering: Proceedings of the 29th Annual Conference of the German Classification Society (GfKl), 2005.
5. [Buitelaar & Cimiano 2006] P. Buitelaar, P. Cimiano: Tutorial Notes of the EACL Tutorial on Ontology Learning from Text, Trento, Italy, 2006.
6. [Brin 1998] S. Brin: Extracting Patterns and Relations from the World Wide Web. Proceedings of the WebDB Workshop at EDBT '98, pp. 172-183, 1998.
7. [Caraballo 1999] S.A. Caraballo: Automatic construction of a hypernym-labeled noun hierarchy from text. Proceedings of the 37th Annual Meeting of the Association for Computational Linguistics (ACL), pp. 120-126, 1999.
8. [Cederberg & Widdows 2003] S. Cederberg, D. Widdows: Using LSA and Noun Coordination Information to Improve the Precision and Recall of Automatic Hyponymy Extraction. Proceedings of the International Conference on Natural Language Learning (CoNLL), pp. 111-118, 2003.
9. [Ciaramita et al. 2005] M. Ciaramita, A. Gangemi, E. Ratsch, J. Saric, I. Rojas: Unsupervised Learning of Semantic Relations between Concepts of a Molecular Biology Ontology. Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), pp. 659-664, 2005.
10. [Cimiano et al. 2006] P. Cimiano, M. Hartung, E. Ratsch: Learning the Appropriate Generalization Level for Relations Extracted from the Genia Corpus. Proceedings of the International Conference on Language Resources and Evaluation (LREC), pp. 161-169, 2006.
11. [Cimiano & Völker 2005a] P. Cimiano, J. Völker: Towards large-scale, open-domain and ontology-based named entity classification. Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP), pp. 166-172, 2005.
12. [Cimiano & Völker 2005b] P. Cimiano, J. Völker: Text2Onto - A Framework for Ontology Learning and Data-driven Change Discovery. Proceedings of the 10th International Conference on Applications of Natural Language to Information Systems (NLDB), volume 3513 of Lecture Notes in Computer Science, pp. 227-238, 2005.
13. [Cimiano and Staab 2005] P. Cimiano, S. Staab: Learning Concept Hierarchies from Text with a Guided Agglomerative Clustering Algorithm. Proceedings of the ICML 2005 Workshop on Learning and Extending Lexical Ontologies with Machine Learning Methods, 2005.
14. [Cimiano et al. 2005] P. Cimiano, A. Hotho, S. Staab: Learning Concept Hierarchies from Text Corpora using Formal Concept Analysis. Journal of Artificial Intelligence Research (JAIR), 24, pp. 305-339, 2005.
15. [Cimiano et al. 2004] P. Cimiano, S. Handschuh, S. Staab: Towards the self-annotating web. Proceedings of the 13th World Wide Web Conference, pp. 462-471, 2004.
16. [Davies et al. 2006] J. Davies, R. Studer, P. Warren: Semantic Web Technologies: Trends and Research in Ontology-based Systems. John Wiley & Sons, 2006.
17. [Etzioni et al. 2004] O. Etzioni, M.J. Cafarella, D. Downey, S. Kok, A.-M. Popesu, T. Shaked, S. Soderland, D.S. Weld, A. Yates: Web-scale information extraction in KnowItAll (preliminary results). Proceedings of the 13th World Wide Web Conference, pp. 100-110, 2004.
18. [Faure & Nedellec 1999] D. Faure, C. Nedellec: Knowledge Acquisition of Predicate Argument Structures from Technical Texts Using Machine Learning: The System ASIUM. Proceedings of the European Knowledge Acquisition Workshop (EKAW), pp. 329-334, 1999.
19. [Frantzi & Ananiadou 1999] K. Frantzi, S. Ananiadou: The C-value/NC-value domain independent method for multi-word term extraction. Journal of Natural Language Processing, 6(3), pp. 145-179, 1999.
20. [Gruber 1995] T.R. Gruber: Towards principles for the design of ontologies used for knowledge sharing. International Journal of Human-Computer Studies, Volume 43, Issue 5-6, pp. 907-928, 1993.
21. [Gruber 2004] Interview for the Official Quarterly Bulletin of AIS Special Interest Group on Semantic Web and Information System 1(3), 2004.
22. [Guarino & Welty 2000] N. Guarino, C.A. Welty: A formal ontology of properties. Knowledge Acquisition, Modeling and Management, pp. 97-112, 2000.
23. [Holsapple & Joshi 2002] C.W. Holsapple, K.D. Joshi: A collaborative approach to ontology design. Communications of the ACM, 45(2), pp. 42-47, 2002.
24. [Mädche & Staab 2000] A. Mädche, S. Staab: Discovering Conceptual Relations from Text. Proceedings of the European Conference on Artificial Intelligence (ECAI), pp. 321-325, 2000.
25. [Manning & Schütze 1999] C.D. Manning, H. Schütze: Foundations of Statistical Natural Language Processing. MIT Press, 1999.
26. [Motik & Sattler 2006] B. Motik, U. Sattler: A Comparison of Techniques for Querying Large Description Logic Aboxes, accepted for publication at the 13th International Conference on Logic for Programming, Artificial Intelligence and Reasoning (LPAR), 2006.
27. [Pantel & Pennacchiotti 2006] P. Pantel, M. Pennacchiotti: Espresso: Leveraging Generic Patterns for Automatically Harvesting Semantic Relations. Proceedings of the Conference on Computational Linguistics/Association for Computational Linguistics (COLING/ACL), 2006.
28. [Paslaru Bontas et al. 2006] E. Paslaru Bontas, C. Tempich, Y. Sure: OntoCom: A Cost Estimation Model for Ontology Engineering. Proceedings of the 5th International Semantic Web Conference (ISWC), 2006.
29. [Pekar & Staab 2003] V. Pekar, S. Staab, Word classification based on combined measures of distributional and semantic similarity. Proceedings of the European Chapter of the Association for Computational Linguistics (EACL), pp. 147-150, 2003.
30. [Pinto & Martins 2004] H.S. Pinto, J.P. Martins: Ontologies: How Can They Be Built? Knowledge and Information Systems, 6(4), pp. 441-464, 2004.
31. [Pinto et al. 2004] H.S. Pinto, S. Staab, C. Tempich: DILIGENT: Towards a fine-grained methodology for DIstributed, Loosely-controlled and evolvInG Engineering of oNTologies. Proceedings of the European Conference on Artificial Intelligence (ECAI), pp. 393-397, 2004.
32. [Schutz & Buitelaar 2005] A. Schutz, P. Buitelaar: RelExt: A Tool for Relation Extraction from Text in Ontology Extension. Proceedings of the 4th International Semantic Web Conference, (ISWC) pp. 593-606, 2005.
33. [Turney 2001] P.D. Turney: Mining the Web for Synonyms: PMI-IR versus LSA on TOEFL. Proceedings of the 12th European Conference on Machine Learning (ECML), pp. 491-502, 2001.
34. [Völker et al. 2005] J. Völker, D. Vrandecic, Y. Sure: Automatic Evaluation of Ontologies (AEON). Proceedings of the 4th International Semantic Web Conference (ISWC), pp. 716-731, 2005.