@inproceedings{hotho03explaining,
title = {Explaining Text Clustering Results using Semantic Structures},
address = {Heidelberg},
author = {Andreas Hotho and Steffen Staab and Gerd Stumme},
booktitle = {Knowledge Discovery in Databases: PKDD 2003, 7th European Conference on Principles and Practice of Knowledge Discovery in Databases},
editor = {Nada Lavra\v c and Dragan Gamberger and Hendrik BlockeelLjupco Todorovski},
pages = {217-228},
publisher = {Springer},
series = {LNAI},
url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2003/hotho2003explaining.pdf},
volume = {2838},
year = {2003},
abstract = {Common text clustering techniques offer rather poor capabilities
for explaining to their users why a particular result has been
achieved. They have the disadvantage that they do not relate
semantically nearby terms and that they cannot explain how
resulting clusters are related to each other.
In this paper, we discuss a way of integrating a large thesaurus
and the computation of lattices of resulting clusters into common text clustering
in order to overcome these two problems.
As its major result, our approach achieves an explanation using an
appropriate level of granularity at the concept level as well as
an appropriate size and complexity of the explaining lattice of
resulting clusters.},
comment = {alpha},
keywords = {analysis clustering concept fca formal ontology semantic text }
}
::