Explaining text clustering results using semantic structures

Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)

Volumn 2838, Issue , 2003, Pages 217-228

  Hotho, Andreas ^a   Staab, Steffen ^a   Stumme, Gerd ^a  

^a UNIVERSITY OF KARLSRUHE   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

INFORMATION RETRIEVAL; INTEGRATION; PROBLEM SOLVING; SEARCH ENGINES; SEMANTICS; VECTORS; CLUSTERING ALGORITHMS; DATABASE SYSTEMS;

INVERSE DOCUMENT FREQUENCY (IDF); SEMANTIC STRUCTURES; TEXT CLUSTERING; VECTOR SPACE; CONCEPT LEVELS;

TEXT PROCESSING; CLUSTER ANALYSIS;

EID: 9444279065     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/978-3-540-39804-2_21     Document Type: Conference Paper

References (19)

1. C. Buckley and A. Lewit. Optimizations of inverted vector searches. InSIGIR-I985, pages 97-110, 1985.
2. William W. Cohen. Fast effective rule induction. In Proc. of ICML-95, pages 115-123. Morgan Kaufmann, July 9-12, 1995.
3. D.R. Cutting, D. R. Karger, J. O. Pedersen, and J. W. Tukey. Scatter/gather: A cluster-based approach to browsing large document collections. In SIGIR-1992, pages 318-329, 1992.
4. S. C. Deerwester, S. T. Dumais, T. K. Landauer, G. W. Furnas, and R. A. Harshman. Indexing by latent semantic analysis. Journal of the American Society of Information Science, 41(6):391-407, 1990.
5. C. Fellbaum, editor. WordNet: An Electronic Lexical Database. The MIT Press, 1998.
6. B. Ganter and R. Wille. Formal Concept Analysis: Mathematical Foundations. Springer, Berlin-Heidelberg, 1999.
7. T. Hofmann. Probabilistic latent semantic indexing. In Research and Development in Information Retrieval, pages 50-57, 1999.
8. A. Hotho, A. Maedche, S. Staab, and R. Studer. SEAL-II - the soft spot between richly structured and unstructured knowledge. Journal of Universal Computer Science (J.UCS), 7(7):566-590, 2001.
9. A. Hotho, S. Staab, and G. Stumme. Wordnet improves text document clustering. In Proc. of the SIGIR 2003 Semantic Web Workshop, 2003.
10. George Karypis and Eui-Hong Han. Fast supervised dimensionality reduction algorithm with applications to document categorization and retrieval. In Proceedings of CIKM-00, pages 12-19. ACM Press, New York, US, 2000.
11. G. Kowalski. Information Retrieval systems-theory and implementations. Kluwer Academic Publishers, 1997.
12. A. Maedche and S. Staab. Ontology learning for the semantic web. IEEE Intelligent Systems, 16(2):72-79, 2001.
13. D. Mladenic. Text learning and related intelligent agents. IEEE Expert, July/August 1999.
14. J. R. Quinlan. C4.5: Programs for Machine Learning. Morgan Kaufmann, San Mateo, California, 1993.
15. C. Van Rijsbergen. Information Retrieval. Buttersworth, London, 1989.
16. G. Salton. Automatic Text Processing: The Transformation, Analysis and Retrieval of Information by Computer. Addison-Wesley, 1989.
17. M. Steinbach, G. Karypis, and V. Kumar. A comparison of document clustering techniques. In KDD Workshop on Text Mining, 2000.
18. G. Stumme, R. Taouil, Y. Bastide, N. Pasqier, and L. Lakhal. Computing iceberg concept lattices with Titanic. J. on Knowledge and Data Engineering, 42:189-222, 2002.
19. O. Zamir, O. Etzioni, O. Madani, and R.M. Karp. Fast and intuitive clustering of web documents. In KDD-1997, pages 287- 290, 1997.