Mohammad, S. & Hirst, G.
(Submitted for publication).
Distributional measures as proxies for semantic relatedness. ,
.
Poelmans, J., Ignatov, D., Viaene, S., Dedene, G. & Kuznetsov, S.
(2012).
Text Mining Scientific Papers: A Survey on FCA-Based Information Retrieval Research.
In
P. Perner (ed.),
Advances in Data Mining. Applications and Theoretical Aspects
, Vol. 7377
(pp. 273-287)
.
Springer Berlin Heidelberg
.
ISBN: 978-3-642-31487-2.
Illig, J. (2008).
Machine Learnability Analysis of Textclassifications in a Social Bookmarking Folksonomy.
Bachelor Thesis
Unpublished master's thesis
, University of Kassel
.
Cimiano, P., Hotho, A. & Staab, S.
(2005).
Learning Concept Hierarchies from Text Corpora using Formal Concept Analysis. Journal on Artificial Intelligence Research,
24, 305-339.
Hotho, A., Staab, S. & Stumme, G.
(2003).
Wordnet improves text document clustering.
Proc. SIGIR Semantic Web Workshop,
Toronto.
Hotho, A., Staab, S. & Stumme, G.
(2003).
Explaining Text Clustering Results using Semantic Structures.
In N. Lavrač, D. Gamberger & H. B. Todorovski (eds.),
Knowledge Discovery in Databases: PKDD 2003, 7th European Conference on Principles and Practice of Knowledge Discovery in Databases (p./pp. 217-228),
Heidelberg: Springer.
Hotho, A., Staab, S. & Stumme, G.
(2003).
Ontologies improve text document clustering.
Proceedings of the 2003 IEEE International Conference on Data Mining (p./pp. 541-544 (Poster),
November 19-22,,
Melbourne, Florida: IEEE Computer Society.
Hotho, A., Staab, S. & Stumme, G.
(2003).
Text Clustering Based on Background Knowledge
(Technical Report ).
University of Karlsruhe, Institute AIFB
.
Hotho, A. & Stumme, G.
(2002).
Conceptual Clustering of Text Clusters.
In G. Kókai & J. Zeidler (eds.),
Proc. Fachgruppentreffen Maschinelles Lernen (FGML 2002) (p./pp. 37-45),
.