Knowledge discovery for semantic web

Semantic Knowledge Management: Integrating Ontology Management, Knowledge Discovery, and Human Language Technologies

Volumn , Issue , 2009, Pages 21-36

  Mladenić, Dunja ^a   Grobelnik, Marko ^a   Fortuna, Blaž ^a   Grćar, Miha ^a  

^a JO EF STEFAN INSTITUTE   (Slovenia)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84861458810     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1007/978-3-540-88845-1_3     Document Type: Chapter

References (38)

1. Agirre E, Ansa O, Hovy E, Martínez D (2000) Enriching very large ontologies using the WWW. In: Proceedings of the First Workshop on Ontology Learning OL-2000. The 14th European Conference on Artificial Intelligence ECAI-2000. Berlin, Germany.
2. Bisson G, Nédellec C, Cañamero D (2000) Designing clustering methods for ontology building: The Mo'K workbench. In: Proceedings of the First Workshop on Ontology Learning OL-2000. The 14th European Conference on Artificial Intelligence ECAI-2000. Berlin, Germany.
3. Brank J, Grobelnik M, Mladenic D (2007a) Automatic evaluation of ontologies. In: Kao and Poteet (eds.) Natural Language Processing and Text Mining, Springer, London: 193-219.
4. Brank J, Grobelnik M, Mladenic D (2007b) Predicting the addition of new concepts in a topic hierarchy. In: Bohenec et al. (eds) Zbornik 10. mednarodne multikonference Informacijska družba IS 2007, 8.-12. oktober 2007: zvezek A: volume A, (Informacijska družba). Ljubljana: Institut "Jožef Stefan": 181-185.
5. Buitelaar P, Cimiano P, Magnini B (2005) Ontology Learning from Text: Methods, Applications and Evaluation, Frontiers in Artificial Intelligence and Applications, IOS Press, Amstredam
6. Chakrabarti S (2002) Mining the Web: Analysis of Hypertext and Semi Structured Data. Morgan Kaufmann, San Francisco.
7. Deerwester S, Dumais S, Furnas G, Landuer T and Harshman R (1990) Indexing by latent semantic analysis. Journal of the American Society of Information Science, Vol. 41 /6: 391-407.
8. Duda R O, Hart P E and Stork D G (2000) Pattern Classification 2nd edition, Wiley, New York.
9. Fayyad U, Piatetski-Shapiro G, Smith P and Uthurusamy R (eds.) (1996) Advances in Knowledge Discovery and Data Mining. MIT Press, Cambridge, MA.
10. Fayyad U, Grinstein G G and Wierse A (eds.) (2001) Information Visualization in Data Mining and Knowledge Discovery, Morgan Kaufmann, San Francisco.
11. Ferlež J, Faloutsos C, Leskovec J, Mladenic D, Grobelnik M (2008) Monitoring network evolution using MDL. In: Proceedings of the IEEE 24th International Conference on Data Engineering ICDE: 1328-1330.
12. Fortuna B, Grobelnik M, Mladenic D (2005) Visualization of text document corpus. Informatica 29: 497-502.
13. Fortuna B, Grobelnik M, Mladenic D (2006a) Background Knowledge for Ontology Construction. WWW 2006, May 23.26, Edinburgh, Scotland.
14. Fortuna B, Grobelnik M, Mladenic D (2006b) Semi-automatic data-driven ontology construction system. In: Proceedings of the 9th International Multi-conference Information Society IS-2006, Ljubljana, Slovenia.
15. Grcar M, Grobelnik M, Mladenic D (2007) Using text mining and link analysis for software. In: Ras V, Zbigniew W, Zighed, Djamel A, Tsumoto, Shusaku (eds). ECML PKDD 2007, The 18th European Conference on Machine Learning and the 11th European Conference on Principles and Practice of Knowledge Discovery in Databases, September 21, 2007, Warsaw, Poland. Proceedings of the Third International Workshop on Mining Comlex Data, MCD 2007: 1-12.
16. Grobelnik M, Mladenic D (2002) Efficient visualization of large text corpora. In: Proceedings of the Seventh TELRI Seminar. Dubrovnik, Croatia.
17. Grobelnik M, Mladenic D (2004) Visualization of news articles. Informatica Journal, Vol. 28, No. 4: 375-380.
18. Grobelnik, M, Mladenic, D (2005) Simple classification into large topic ontology of Web documents. Journal of Computing and Information Technology - CIT 13, 2005, 4, 279-285.
19. Grobelnik M, Mladenic D (2006) Knowledge discovery for ontology construction. In: John Davies, Studer Rudi, Warren Paul, (eds) Semantic Web Technologies. Wiley, Chichester: 9-27.
20. Grobelnik M, Brank J, Mladenic D, Novak B, Fortuna B (2006) Using DMoz for constructing ontology from data stream. In: Proceedings of the 28th International Conference on Information Technology Interfaces ITI 2006, 19-22 June, Cavtat, Croatia (IEEE Catalog, No. 06EX1244). Zagreb: University of Zagreb, SRCE University Computing Centre: 439-444.
21. Grobelnik M, Brank J, Fortuna B, Mozetic I (2008) Contextualizing ontologies with ontolight a pragmatic approach. Informatica, Vol. 32, No. 1: 79-84.
22. Hand DJ, Mannila H. Smyth P (2001) Principles of Data Mining (Adaptive Computation and Machine Learning), MIT Press, Cambridge, MA.
23. Hastie T, Tibshirani R and Friedman J H (2001) The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Springer Series in Statistics, Springer, New York.
24. Jain A K, Murty M N, and Flynn P J (1999) Data Clustering: A Review. ACM Computing Surveys, Vo l 31 /3: 264-323.
25. Joachims T (1999) Making large-scale svm learning practical. In: Scholkopf et al. (eds) Advances in Kernel Methods, Support Vector Learning, MIT, Cambridge, MA.
26. Jörg B, Jermol M, Uszkoreit H, Grobelnik M, Frlež J, Kiryakov A (2006) Analytical information services for the European research area. V: CUNNINGHAM, Paul (ed), CUNNINGHAM, Miriam (ed). Exploiting the knowledge economy: issues, applications and case studies, (Information and communication technologies and the knowledge economy, Vol. 3. IOS Press Amsterdam: 1367-1395.
27. Kim H R, Chan P K (2003) Learning implicit user interest hierarchy for context in personalization. In Proceedings of the 8th Iinternational Conference on Intelligent user Interfaces IUI, ACM Press, New York: 101-108.
28. Mitchell T M (1997) Machine Learning. McGraw-Hill.
29. Mladenic D (1998) Turning Yahoo into an automatic Web-page classifier. In: Proceedings of the13th European Conference on Artificial Intelligence ECAI 98. Wiley, Chichester: 473-474.
30. Mladenic D, Grobelnik M (2005) Visualizing very large graphs using clustering neighborhoods. In: Morik et al. (eds.) Local Pattern Detection: International Seminar: Dagstuhl Castle, Germany, April 12-16, 2004: revised selected papers, Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence) vol. 3539, State-of-the-art survey. Springer, Berlin Heidelberg 89-97.
31. Mladenic D, Grobelnik M (2007) Evaluation of semi-automatic ontology generation in realworld setting. In: Proceedings of the 29th International Conference on Information Technology Interfaces, June 25-28, 2007, Cavtat/Dubrovnik, Croatia. ITI 2007 (IEEE Catalog, No. 07EX1589). University of Zagreb, Zagreb SRCE University Computing Centre: 547-551.
32. Salton G, Buckley C (1990) Improving Retrieval Performance by Relevance Feedback. Journal of the American Society for Information Science, Vol. 41, 4: 288-297.
33. Salton G (1991) Developments in automatic text retrieval. Science, Vol. 253: 974-979.
34. Steinbach M, Karypis G, Kumar V (2000) A comparison of document clustering techniques. In: Proceedings of KDD-2000 Workshop on Text Mining: 109-110.
35. Tong S, Koller D (2000) Support Vector machine active learning with applications to text classification. In: Proceedings of 17th International Conference on Machine Learning (ICML).
36. Tresp V, Bundschus M, Rettinger A, Huang Y (2008) Towards Machine Learning on the Semantic Web. In: d'Amato et al. (eds.) Uncertainty Reasoning for the Semantic Web I. Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence) vol. 5327, Springer, Berlin Heidelberg.
37. van Rijsbergen, C J (1979) Information Retrieval. 2nd Edition. Butterworths, London.
38. Witten I H, Frank E (1999) Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations, Morgan Kaufmann, San Francisco.