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References on Ontologies:

  1. J. De Bruijn. Using ontologies. enabling knowledge sharing and reuse on the semantic web. Technical report, DERI, 2003. Available at: http://homepage.uibk.ac.at/~c703239/publications/DERI-TR-2003-10-29.pdf.
  2. R. Studer, V.R. Benjamins, and Fensel D. Knowledge engineering: Principles and methods. Data and Knowledge Engineering (DKE), 25:161–197, 1998.
  3. T.R. Gruber. Toward principles for the design of ontologies used for knowledge sharing. International Journal Of Human Computer Studies, 43(5/6):907–928, 1995.

 

References on Ontology Learning:

  1. A. Gomez-Perez and D. Manzano-Macho. A survey of ontology learning methods and techniques. Technical report. Ontology-based Information exchange for Knowledge Management and Electronic Commerce, Deliverable 1.5.
  2. P. Buitelaar, D. Olejnic, and M. Sintek. A protege plug-in for ontology extraction from text based on linguistic analysis. In Proceedings of the 1st European Semantic Web Symposium, 2004.
  3. A. Maedche and S. Staab. Ontology Learning. Springer, 2004.
  4. P. Cimiano and J. Volker. Text2Onto. A Framework for Ontology Learning and Data-Driven Change Discovery, pages 227–238. Springer-Verlag, 2005.
  5. M. Missikoff, R. Navigli, and P. Velardi. Integrated approach to web ontology learning and engineering. IEEE Computer Journal, pages 54–57, 2002.
  6. R. Navigli and P. Velardi. Ontology learning and its application to automated terminology translation. IEEE Intelligent Systems, 18(1), 2003.
  7. R. Navigli and P. Velardi. Learning Domain Ontologies from Document Warehouses and Dedicated Web Sites. MIT Press, 2004.
  8. M. Missikoff, R. Navigli, and P. Velardi. The usable ontology: An environment for building and assessing a domain ontology. In International Semantic Web Conference (ISWC), Sardinia, Italia, 2002.
  9. A. Pivk. Automatic ontology generation from web tabular structures. AI Communications, 19:83–85, 2006.
  10. M. Sabou. Learning Web Service Ontologies: an Automatic Extraction Method and its Evaluation. IOS Press, 2005.
  11. L. Stojanovic, N. Stojanovic, and R. Volz. Migrating data-intensive web sites into the semantic web. In Proceedings of the 17th ACM Symposium on Applied Computing, pages 1100–1107. ACM Press, 2002.
  12. P. Johannesson. A method for transforming relational schemas into conceptual schemas. In Proceedings of the 10th International Conference on Data Engineering, Ed. M. Rusinkiewicz, pages 115–122. IEEE Press, 1994.

 

References on Ontology Learning tools:

  1. ASIUM: D. Faure and C. Nedellec. Knowledge acquisition of predicate argument structures from technical texts using machine learning: The system asium. In D. Fensel and R. Studer editors, Proc. of the 11th European Workshop (EKAW’99), LNAI 1621, pages 329–334. Springer Verlag, 1999.
  2. DOE: B. Bachimont.     Engagement s ́mantique et engagement ontologique: Conception et réalisation d’ontologies an ingénierie des connaissances. In Ingenierie des Connaissances: Evolutions Récentes et Nouveaux Defis, Eyrolles, 2000.
  3. OntoLearn: M. Missikoff, R. Navigli, and P. Velardi. Integrated approach to web ontology learning and engineering. IEEE Computer Journal, pages 54–57, 2002.
  4. TextToOnto: A. Maedche and R. Volz. The text-to-onto ontology extraction and maintenance environment. In Proceedings of the ICDM Workshop
    on Integrating Data Mining and Knowledge Management, 2001.
  5. OntoLT: P. Buitelaar, D. Olejnic, and M. Sintek. A protege plug-in for ontology extraction from text based on linguistic analysis. In Proceedings of the 1st European Semantic Web Symposium, 2004.
  6. KAON: A. Maedche and S. Staab. Ontology Learning. Springer, 2004.
  7. OntoBasis: The ontobasis project, http://wise.vub.ac.be/ontobasis.
  8. ATTRACT: H. Mima, S. Ananiadou, and G. Nenadic. The atract workbench: Automatic term recognition and clustering for terms. In Proceedings of the 4th International Conference on Text, Speech and Dialogue, LNCS, volume 2166. Springer-Verlag, 2001.
  9. TERMINAE: B. Biebow and S. Szulman. Terminae: a linguistic-based tool for the building of a domain ontology. In Proceedings of the 11th European Workshop on Knowledge Acquisition, Modelling and Management, pages 49–66. Springer Verlag, 1999.
  10. KEA: S. Jones and G.W. Paynter. Automatic extraction of document keyphrases for use in digital libraries: Evaluation and applications. Journal of the American Society for Information Science and Technology, 53(8):653–677, 2002.
  11. CAMELEON: N. Aussenac-Gilles and P. Seguela. Les relations sémantiques: Du linguistique au formel. Cahiers de Grammaire, No. Special sur la Linguistique de Corpus, 25:175–198, 2000.
  12. T-REX: J. Iria. T-rex: A flexible relation extraction framework. In Proceedings of the 8th Annual CLUK Research Colloquium, 2005.
  13. HASTI: M. Shamsfard and A.A. Barforoush. Ontology learning from natural language texts. International Journal of Human-Computer Studies, 2002.
  14. SVETLAN': G. Chalendar and B. Gray. Svetlan’: A system to classify nouns in context. In Proceedings of the ECAI 2000 Workshop on Ontology Learning, 2001.
  15. SYNDICATE: U. Hahn and M. Romacker. The syndikate text knowledge base generator. In Proceedings of the 1st International Conference on Human Language Technology Research, pages 328–333, 2001.
  16. DODDLE II: T. Yamaguchi. Acquiring conceptual relations from domainspecific texts. In Proceedings of the IJCAI 2001 Workshop on Ontology Learning, 2001.

 

References on Concept Identification:

  1. M. Krauthammer and G. Nenadic. Term identification in the biomedical literature. Journal of Biomedical Informatics, 37:512–526, 2004.
  2. A. Saltion, G. Wong and C.S. Yang. A vector space model for automatic indexing. Communications of the ACM, 18(11):613–620, 1975.
  3. K. Ahmad, A. Davies, H. Fulford, and M. Rogers. What is a term? The Semi-Automatic Extraction of Terms from Text. Amsterdam: John Benjamins Publishing Company, 1994.
  4. F.J. Damerau. Evaluating domain-oriented multiword terms from texts. Information Processing and Management, 29(4):433–447, 1993.
  5. B. Fortuna, D. Mladevic, and M. Grobelnik. Visualization of text document corpus. In ACAI 2005 Summer School, 2005.
  6. K. Frantzi, S. Ananiadou, and H. Mima. Automatic recognition of multi-word terms: The c-value/nc-value method. International Journal on Digital Libraries, 3(2):115–130, 2000.
  7. J.U. Kietz, A. Maedche, and R. Volz. A method for semi-automatic ontology acquisition from a corporate intranet. In Proceedings of the ECAW-2000 Workshop on Ontologies and Text, 2000.
  8. E. Agirre, O. Ansa, E. Hovy, and D. Martinez. Enriching very large ontologies using the www. In Proceedings of the ECAI-00 Workshop on Ontology Construction, 2000.
  9. C. Fellbaum. WordNet: An On-Line Lexical Database and Some of its Applications. Cambridge: MIT Press, 1998.
  10. A. Faatz and R. Steinmetz. Ontology enrichment with texts from the www. In Proceedings of the ECML/PKDD Workshop on Semantic Web Mining, 2002.
  11. Dias G. and S. Guillore. Multilingual aspects of multiword lexical units. In Proceedings of the Language Technologies - Multilingual Aspects Workshop, pages 11–21, 1999.
  12. S.F. Dennis. The Design and Testing of a Fully Automated Indexing-Searching System for Documents Consisting of Expository Test. Washington D.C.: Thompson Book, 1967.
  13. M. Nagao, M. Mizutani, and H. Ikeda. An automated method of the extraction of important words from japanese scientific documents. Transactions of Information Processing Society of Japan, 17(2):110–117, 1976.
  14. G. Salton, C.S. Yang, and C.T. Yu. A theory of term importance in automatic text analysis. Journal of the American Society for Information Science, 26(1):33–44, 1975.
  15. T. Griffiths and M. Steyvers. A probabilistic approach to semantic representation. In Proceedings of the Twenty-Fourth Annual Conference of the Cognitive Science Society, pages 381–386, 2002.
  16. T. Hofmann. Probabilistic latent semantic indexing. In Proceedings of the Twenty-Second Annual International SIGIR Conference on Research and Development in Information Retrieval, 1999.
  17. D.M. Blei, A.Y. Ng, and M.I. Jordan. Latent dirichlet allocation. Journal of Machine Learning Research, 3:993–1022, 2003.
  18. N. Collier, C. Nobata, and J. Tsujii. Extracting the names of genes and gene products with a hidden markov model. In Proceedings of the 18th conference on Computational linguistics, pages 201–207, 2000.
  19. L.L. Earl. Experiments in automatic extracting and indexing. Information Storage and Retrieval, 6:273–288, 1970.
  20. L.L. Earl. The resolution of syntactic ambiguity in language processing. Information Storage and Retrieval, 8(6):277–308, 1972.
  21. A. Arppe. Term extraction from unrestricted text. In NODALIDA 95, Helsinki, 1995.
  22. J.S. Justeson and S.M. Katz. Technical terminology: Some linguistic properties and an algorithm for identification in text. Natural Language Engineering, 1(1):9–27, 1995.
  23. D.I. Moldovan and R.C. Girju. An interactive tool for the rapid development of knowledge bases. International Journal on Artificial Intelligence Tools (IJAIT), 10(1-2), 2001.
  24. J.D. Cohen. Highlights: Language and domain independent automatic indexind terms for abstracting. Journal of the American Society for Information Science, 46(3):162–174, 1995.
  25. U. Heid. A linguistic bootstrapping approach to the extraction of term candidates from german text. Terminology, 5(2):161–181, 1998.
  26. C. Enguehard and L. Pantera. Automatic natural acquisition of a terminology. Journal of Quantitative Linguistics, 2(1):27–32, 1994.

 

References on Hierarchy Construction:

  1. H.F. Witschel. Using decision trees and text mining techniques for extending taxonomies. In Proceedings of Learning and Extending Lexical Ontologies by Using Machine Learning Methods, Workshop at ICML-05, 2005.
  2. E. Alfonseca and S. Manandhar. Extending a lexical ontology by a combination of distributional semantic signatures. In In Proceedings of the 13th International Conference on Knowledge Engineering and Knowledge Management, pages 1–7. Springer, 2002.
  3. A. Faatz, S. Hormann, C. Seeberg, and R. Steinmetz. Conceptual enrichment of ontologies by means of a generic and configurable approach. In Proceedings of the ESSLI 2001 Workshop on Semantic Knowledge Acquisition and Categorism, 2001.
  4. V. Pekar and S. Staab. Word classification based on combined measures of distributional and semantic similarity. In Proceedings of the Research Note Sessions of the 10th Conference of the European Chapter of the Association for the Computational Linguistics, 2003.
  5. P. Cimiano and S. Staab. Learning by googling. SIGKDD Explorations, 6(2):24–33, 2004.
  6. D. Faure and C. Nedellec. Asium: Learning subcategorization frames and restrictions of selection. In 10th European Conference on Machine Learning, ECML98, Workshop on Text Mining, 1998.
  7. E. Gaussier, C. Goutte, K. Popat, and F. Chen. A hierarchical model for clustering and categorising documents. In Advances in Information Retrieval - Proceedings of the 24th BCS-IRSG European Colloquium on IR Research, pages 229–247. Springer, 2002.
  8. G. Paaß, J. Kindermann, and E. Leopold. Learning prototype ontologies by hierarchical latent semantic analysis. In In Knowledge Discovery and Ontologies (KDO-2004), 2004.
  9. M.A. Hearst. Automatic acquisition of hyponyms from large text corpora. In Proceedings of the 14th International Conference on Computational Linguistics, 1992.
  10. L.M. Iwanska, N. Mata, and K. Kruger. Fully Automatic Acquisition of Taxonomic Knowledge from Large Corpora of Texts, pages 335–345. MIT/AAAI Press, 2000.
  11. O. Etzioni, M. Cafarella, D. Downey, S. Kok, A. Popescu, T. Shaked, S. Soderland, D. Weld, and A. Yates. Web-scale information extraction in knowitall (preliminary results). In Proceedings of 13th World Wide Web Conference, pages 100–109, 2004.
  12. P. Cimiano, A. Pivk, L. Schmidt-Thieme, and S. Staab. Learning taxonomic relations from heterogeneous evidence. In European Conference on Artificial Intelligence (ECAI 2004), Workshop on Ontology Learning, 2004.
  13. O. Downey, D. Etzioni, S. Soderland, and D. Weld. Learning text patterns for web information extraction and assessment. In Proceedings of the AAAI Workshop on Adaptive Text Extraction and Mining, 2004.
  14. R. Snow, D. Jurafsky, and A.Y. Ng. Learning syntactic patterns for automatic hypernym discovery. In Proceedings of Advances in Neural Information Processing Systems, 2004.
  15. E. Agichtein and L. Gravano. Snowball: Extracting relations from large plain-text collections. In Proceedings of the 5th ACM International Conference on Digital Libraries (ACM DL), pages 85–94, 2000.
  16. F. Rinaldi and E. Yuste. Exploiting Technical Terminology for Knowledge Management. IOS Press, 2005.
  17. B. Bachimont, A. Isaac, and R. Troncy. Semantic Commitment for Designing Ontologies: a Proposal, pages 114–121. Springer Verlag, Berlin Heidelberg, 2002.

 

References on Semantic Relation Extraction:

  1. E. Charniak and M. Berland. Finding parts in very large corpora. In Proceedings of the 37th Annual Meeting of the ACL, pages 57–64, 1999.
  2. P. Cimiano and J. Wenderoth. Automatically learning qualia structures from the web. In Proceedings of the ACL Workshop on Deep Lexical Acquisition, pages 28–37, 2005.
  3. I. Yamada and T. Baldwin. Automatic discovery of tellic and agentive roles from corpus data. In Proceedings of the 18th Pacific Asia Conference on Language, Information and Computation (PACLIC 18), 2004.
  4. R. Girju and D.L. Moldovan. Text mining for causal relations. In Text Mining for Causal Relation, pages 360–364, 2002.
  5. M. Poesio and A. Almuhareb. Identifying concept attributes using a classifier. In Proceedings of the ACL Workshop on Deep Lexical Acquisition, pages 18–27, 2005.
  6. A. Maedche and S. Staab. Semi-automatic engineering of ontologies from text. In Proceedings of the 12th International Conference on Software Engineering and Knowledge Engineering, 2000.
  7. A. Maedche and S. Staab. Discovering conceptual relations from text. In Proceedings of ECAI 2000, IOS Press, Amsterdam, 2000.
  8. R. Srikant and R. Agrawal. Mining generalized association rules. In Proceedings of VLDB ’95, pages 407–419, 1995.
  9. A. Maedche and S. Staab. Ontology learning for the semantic web. IEEE Intelligent Systems, 16:72–79, 2001.
  10. M. Kavalec and V. Svatek. A Study on Automated Relation Labelling in Ontology Learning, pages 44–58. IOS Press, 2005.
  11. C. Roux, D. Proux, F. Rechenmann, and L. Julliard. An ontology enrichment method for a pragmatic information extraction system gathering data on genetic interactions. In In ECAI-2000 Workshop on Ontology Learning, 2000.
  12. S. Schulte im Walde. Clustering verbs semantically according to their alternation behaviour. In Proceedings of the 18th International Conference on Computational Linguistics (COLINGS), pages 747–753, 2000.
  13. J. Saric, L.J. Jensen, R. Ouzounova, I. Rojas, and P. Bork. Extraction of regulatory gene expression networks from pubmed. In Proceedings of the 42nd Annual Meeting of the Association for Computational Linguistics, 2004.
  14. B. Rosario and M. Hearst. Classifying semantic relations in bioscience text. In In Proceedings of the 42nd Annual Meeting of the Association for Computational Linguistics, 2004.
  15. N. Aussenac-Gilles, B. Biebow, and S. Szulman. Corpus analysis for conceptual modelling. In In EKAW-2000 Workshop on Ontologies and Text, Knowledge Engineering and Knowledge Management: Methods, Models and Tools. Springer Verlag, 2000.
  16. N. Aussenac-Gilles, B. Biebow, and S. Szulman. Revisiting ontology design: A methodology based on corpus analysis. In In 12th International Conference in Knowledge Engineering and Knowledge Management, pages 172–188. Springer Verlag, Lecture Notes in Artificial Intelligence (LNAI) 1937, 2000.
  17. D. Lonsdale, Y. Ding, D.W. Embley, and A. Melby. Peppering knowledge sources with salt; boosting conceptual content for ontology generation. In Proceedings of the AAAI Workshop on Semantic Web Meets Language Resources, 2002.
  18. M. Ciaramita, A. Gangemi, E. Ratsch, J. Saric, and I. Rojas. Unsupervised learning of semantic relations between concepts of a molecular biology ontology. In In Proceedings of the 19th International Joint Conference on Artificial Intelligence, 2005.
  19. A. Wagner. Enriching a lexical semantic net with selectional preferences by means of statistical corpus analysis. In Proceedings of the ECAI-2000 Workshop on Ontology Learning, pages 37–42, 2000.
  20. J. Iria. T-rex: A flexible relation extraction framework. In Proceedings of the 8th Annual CLUK Research Colloquium, 2005.