Learning Ontologies to Improve Text Clustering and Classification-Reference-Cited by-同舟云学术

Learning Ontologies to Improve Text Clustering and Classification

Published: Issue: Volume: Page:334-341
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Container-title:From Data and Information Analysis to Knowledge Engineering
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Author:

Bloehdorn Stephan,Cimiano Philipp,Hotho Andreas

Publisher

Springer-Verlag

Link

http://link.springer.com/content/pdf/10.1007/3-540-31314-1_40.pdf

Reference20 articles.

1. BLOEHDORN, S. and HOTHO, A. (2004): Text Classification by Boosting Weak Learners based on Terms and Concepts. In: Proceedings of ICDM, 2004. IEEE Computer Society.

2. CAI, L. and HOFMANN, T. (2003): Text Categorization by Boosting Automatically Extracted Concepts. In: Proceedings of ACM SIGIR, 2003. ACM Press.

3. CIMIANO, P.; HOTHO, A. and STAAB, S. (2004): Comparing Conceptual, Partitional and Agglomerative Clustering for Learning Taxonomies from Text. In: Proceedings of ECAI’04. IOS Press.

4. CIMIANO, P. and HOTHO, A. and STAAB, S. (2005): Learning Concept Hieararchies from Text Corpora using Formal Concept Analysis. Journal of Artificial Intelligence Research. To appear.

5. DEERWESTER, S.; DUMAIS, S.T.; LANDAUER, T.K.; FURNAS, G. W. and HARSHMAN, R.A. (1990): Indexing by Latent Semantic Analysis. Journal of the Society for Information Science, 41, 391–407.

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