next up previous
Next: About this document ... Up: Learning Concept Hierarchies from Previous: Mutually Similar Terms

Bibliography

1
E. Agirre, O. Ansa, E. Hovy, and D. Martinez.
Enriching very large ontologies using the WWW.
In Proceedings of the ECAI Ontology Learning Workshop, 2000.

2
K. Ahmad, M. Tariq, B. Vrusias, and C. Handy.
Corpus-based thesaurus construction for image retrieval in specialist domains.
In Proceedings of the 25th European Conference on Advances in Information Retrieval (ECIR), pages 502-510, 2003.

3
R. Basili, M.T. Pazienza, and M. Vindigni.
Corpus-driven unsupervised learning of verb subcategorization frames.
In Proceedings of the 5th Congress of the Italian Association for Artificial Intelligence (AI*IA97), 1997.

4
Radim Belohlavek.
Similarity relations in concept lattices.
Journal of Logic and Computation, 10(6):823-845, 2000.

5
G. Bisson, C. Nédellec, and L. Canamero.
Designing clustering methods for ontology building - The Mo'K workbench.
In Proceedings of the ECAI Ontology Learning Workshop, pages 13-19, 2000.

6
Stephan Bloehdorn and Andreas Hotho.
Text classification by boosting weak learners based on terms and concepts.
In Proceedings of the 4th IEEE International Conference on Data Mining (ICDM), pages 331-334, 2004.

7
C. Brewster, F. Ciravegna, and Y. Wilks.
Background and foreground knowledge in dynamic ontology construction.
In Proceedings of the SIGIR Semantic Web Workshop, 2003.

8
S.A. Caraballo.
Automatic construction of a hypernym-labeled noun hierarchy from text.
In Proceedings of the 37th Annual Meeting of the Association for Computational Linguistics (ACL), pages 120-126, 1999.

9
C. Carpineto and G. Romano.
A lattice conceptual clustering system and its application to browsing retrieval.
Machine Learning, 24:95-122, 1996.

10
E. Charniak and M. Berland.
Finding parts in very large corpora.
In Proceedings of the 37th Annual Meeting of the Association for Computational Linguistics (ACL), pages 57-64, 1999.

11
G. Chartrand, G. Kubicki, and M. Schultz.
Graph similarity and distance in graphs.
Aequationes Mathematicae, 55(1-2):129-145, 1998.

12
P. Cimiano.
Ontology-driven discourse analysis in GenIE.
In Proceedings of the 8th International Conference on Applications of Natural Language to Information Systems, pages 77-90, 2003.

13
P. Cimiano, S. Handschuh, and S. Staab.
Towards the self-annotating web.
In Proceedings of the 13th World Wide Web Conference, pages 462-471, 2004.

14
P. Cimiano, A. Hotho, and S. Staab.
Clustering ontologies from text.
In Proceedings of the 4th International Conference on Language Resources and Evaluation (LREC), pages 1721-1724, 2004.

15
P. Cimiano, A. Hotho, and S. Staab.
Comparing conceptual, divisive and agglomerative clustering for learning taxonomies from text.
In Proceedings of the European Conference on Artificial Intelligence (ECAI), pages 435-439, 2004.

16
P. Cimiano, G. Ladwig, and S. Staab.
Gimme' the context: Context-driven automatic semantic annotation with C-PANKOW.
In Proceedings of the 14th World Wide Web Conference, 2005.

17
P. Cimiano, A. Pivk, L. Schmidt-Thieme, and S. Staab.
Learning taxonomic relations from heterogeneous sources.
In Proceedings of the ECAI 2004 Ontology Learning and Population Workshop, 2004.

18
P. Cimiano, A. Pivk, L. Schmidt-Thieme, and S. Staab.
Learning taxonomic relations from heterogeneous evidence.
In P. Buitelaar, P. Cimiano, and B. Magnini, editors, Ontology Learning from Text: Methods, Applications and Evaluation. IOS Press, 2005.
to appear.

19
P. Cimiano, S.Staab, and J. Tane.
Automatic acquisition of taxonomies from text: FCA meets NLP.
In Proceedings of the PKDD/ECML'03 International Workshop on Adaptive Text Extraction and Mining (ATEM), pages 10-17, 2003.

20
P. Cimiano and S. Staab.
Learning by googling.
SIGKDD Explorations, 6(2):24-34, December 2004.

21
P. Cimiano, S. Staab, and J. Tane.
Deriving concept hierarchies from text by smooth formal concept analysis.
In Proceedings of the GI Workshop "Lehren Lernen - Wissen - Adaptivität" (LLWA), pages 72-79, 2003.

22
W. Day and H. Edelsbrunner.
Efficient algorithms for agglomerative hierarchical clustering methods.
Journal of Classification, 1:7-24, 1984.

23
R. O. Duda, P. E. Hart, and D. G. Stork.
Pattern Classification.
John Wiley & Sons, Inc., 2001.

24
D. Faure and C. Nédellec.
A corpus-based conceptual clustering method for verb frames and ontology.
In P. Velardi, editor, Proceedings of the LREC Workshop on Adapting lexical and corpus resources to sublanguages and applications, pages 5-12, 1998.

25
B. Ganter and K. Reuter.
Finding all closed sets: A general approach.
Order, 8:283-290, 1991.

26
B. Ganter and R. Wille.
Formal Concept Analysis - Mathematical Foundations.
Springer Verlag, 1999.

27
R. Girju and M. Moldovan.
Text mining for causal relations.
In Proceedings of the FLAIRS Conference, pages 360-364, 2002.

28
W. Goddard and H.C. Swart.
Distance between graphs under edge operations.
Discrete Mathematics, 161:121-132, 1996.

29
R. Godin, R. Missaoui, and H. Alaoui.
Incremental concept formation algorithms based on galois (concept) lattices.
Computational Intelligence, 11(2):246-267, 1995.

30
G. Grefenstette.
Explorations in Automatic Thesaurus Construction.
Kluwer, 1994.

31
Gregory Grefenstette.
Evaluation techniques for automatic semantic extraction: Comparing syntactic and window-based approaches.
In Proceedings of the Workshop on Acquisition of Lexical Knowledge from Text, 1992.

32
Z. Harris.
Mathematical Structures of Language.
Wiley, 1968.

33
M.A. Hearst.
Automatic acquisition of hyponyms from large text corpora.
In Proceedings of the 14th International Conference on Computational Linguistics (COLING), pages 539-545, 1992.

34
D. Hindle.
Noun classification from predicate-argument structures.
In Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL), pages 268-275, 1990.

35
A. Hotho, S. Staab, and G. Stumme.
Ontologies improve text document clustering.
In Prodeedings of the IEEE International Conference on Data Mining (ICDM), pages 541-544, 2003.

36
L.M. Iwanska, N. Mata, and K. Kruger.
Fully automatic acquisition of taxonomic knowledge from large corpora of texts.
In L.M. Iwanksa and S.C. Shapiro, editors, Natural Language Processing and Knowledge Processing, pages 335-345. MIT/AAAI Press, 2000.

37
Lillian Lee.
Measures of distributional similarity.
In 37th Annual Meeting of the Association for Computational Linguistics (ACL), pages 25-32, 1999.

38
C. Lindig.
Fast concept analysis.
In G. Stumme, editor, Proceedings of the International Conference on Conceptual Structures (ICCS). Shaker Verlag, Aachen, Germany, 2000.

39
A. Maedche, V. Pekar, and S. Staab.
Ontology learning part one - on discovering taxonomic relations from the web.
In Proceedings of the Web Intelligence conference, pages 301-322. Springer Verlag, 2002.

40
A. Maedche and S. Staab.
Measuring similarity between ontologies.
In Proceedings of the European Conference on Knowledge Engineering and Knowledge Management (EKAW), pages 251-263. Springer Verlag, 2002.

41
Alexander Maedche and Steffen Staab.
Discovering conceptual relations from text.
In W. Horn, editor, Proceedings of the 14th European Conference on Artificial Intelligence (ECAI), 2000.

42
P.E. Maher.
A similarity measure for conceptual graphs.
Intelligent Systems, 8:819-837, 1993.

43
C. Manning and H. Schuetze.
Foundations of Statistical Language Processing.
MIT Press, 1999.

44
K. Markert, N. Modjeska, and M. Nissim.
Using the web for nominal anaphora resolution.
In EACL Workshop on the Computational Treatment of Anaphora, 2003.

45
S.H. Myaeng and A. Lopez-Lopez.
Conceptual graph matching: A flexible algorithm and experiments.
Experimental and Theoretical Artificial Intelligence, 4:107-126, 1992.

46
F. Pereira, N. Tishby, and L. Lee.
Distributional clustering of english words.
In Proceedings of the 31st Annual Meeting of the Association for Computational Linguistics (ACL), pages 183-190, 1993.

47
Wiebke Petersen.
A set-theoretical approach for the induction of inheritance hierarchies.
Electronic Notes in Theoretical Computer Science, 51, 2002.

48
M. Poesio, T. Ishikawa, S. Schulte im Walde, and R. Viera.
Acquiring lexical knowledge for anaphora resolution.
In Proceedings of the 3rd Conference on Language Resources and Evaluation (LREC), 2002.

49
Uta Priss.
Linguistic applications of formal concept analysis.
In G. Stumme and R. Wille, editors, Formal Concept Analysis - State of the Art. Springer, 2004.

50
M.-L. Reinberger and P. Spyns.
Unsupervised text mining for the learning of dogma-inspired ontologies.
In P. Buitelaar, P. Cimiano, and B. Magnini, editors, Ontology Learning from Text: Methods, Evaluation and Applications. IOS Press, 2005.
to appear.

51
Philip Resnik.
Selectional preference and sense disambiguation.
In Proceedings of the ACL SIGLEX Workshop on Tagging Text with Lexical Semantics: Why, What, and How?, 1997.

52
M. Sanderson and B. Croft.
Deriving concept hierarchies from text.
In Research and Development in Information Retrieval, pages 206-213. 1999.

53
H. Schmid.
Probabilistic part-of-speech tagging using decision trees.
In Proceedings of the International Conference on New Methods in Language Processing, 1994.

54
Helmut Schmid.
Lopar: Design and implementation.
In Arbeitspapiere des Sonderforschungsbereiches 340, number 149. 2000.

55
R. Sibson.
SLINK: an optimally efficient algorithm for the single-link cluster method.
The Computer Journal, 16(1):30-34, 1973.

56
Caroline Sporleder.
A galois lattice based approach to lexical inheritance hierarchy learning.
In Proceedings of the ECAI Workshop on Machine Learning and Natural Language Processing for Ontology Engineering (OLT 2002), 2002.

57
S. Staab, C. Braun, I. Bruder, A. Düsterhöft, A. Heuer, M. Klettke, G. Neumann, B. Prager, J. Pretzel, H.-P. Schnurr, R. Studer, H. Uszkoreit, and B. Wrenger.
Getess - searching the web exploiting german texts.
In Proceedings of the 3rd Workshop on Cooperative Information Agents, pages 113-124. Springer Verlag, 1999.

58
M. Steinbach, G. Karypis, and V. Kumar.
A comparison of document clustering techniques.
In KDD Workshop on Text Mining, 2000.

59
Gerd Stumme, Marc Ehrig, Siegrfried Handschuh, Andreas Hotho, Alexander Maedche, Boris Motik, Daniel Oberle, Christoph Schmitz, Steffen Staab, Ljiljana Stojanovic, Nenad Stojanovic, Rudi Studer, York Sure, Raphael Volz, and Valentin Zacharias.
The karlsruhe view on ontologies.
Technical report, University of Karlsruhe, Institute AIFB, 2003.

60
P. Velardi, P. Fabriani, and M. Missikoff.
Using text processing techniques to automatically enrich a domain ontology.
In Proceedings of the International Conference on Formal Ontology in Information Systems (FOIS), pages 270-284, 2001.

61
P. Velardi, R. Navigli, A. Cuchiarelli, and F. Neri.
Evaluation of ontolearn, a methodology for automatic population of domain ontologies.
In P. Buitelaar, P. Cimiano, and B. Magnini, editors, Ontology Learning from Text: Methods, Evaluation and Applications. IOS Press, 2005.
to appear.

62
E.M. Voorhees.
Query expansion using lexical-semantic relations.
In Proceedings of the 17th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 61-69, 1994.

63
K. Zhang, R. Statman, and D. Shasha.
On the editing distance between unordered labeled trees.
Information Processing Letters, 42(3):133-139, 1992.

64
K. Zhang, J.T.L. Wang, and D. Shasha.
On the editing distance between undirected acyclic graphs.
International Journal of Foundations of Computer Science, 7(1):43-57, 1996.

65
G. Zipf.
Selective Studies and the Principle of Relative Frequency in Language.
Cambridge, 1932.






































































































































Philipp Cimiano 2005-08-04