Publikation
Multilingual Evidence Improves Clustering-based Taxonomy Extraction
Hans Hjelm; Paul Buitelaar
In: Malik Ghallab; C.D. Spyropoulos; N. Fakotatis; N. Avouris (Hrsg.). Proceedings of the 18th European Conference on Artificial Intelligence. European Conference on Artificial Intelligence (ECAI-2008), 18th, July 21-25, Patras, Greece, Pages 288-292, Frontiers in Artificial Intelligence and Applications, Vol. 178, IOS Press, 2008.
Zusammenfassung
We present a system for taxonomy extraction, aimed at
providing a taxonomic backbone in an ontology learning environment.
We follow previous research in using hierarchical clustering
based on distributional similarity of the terms in texts. We show that
basing the clustering on a comparable corpus in four languages gives
a considerable improvement in accuracy compared to using only the
monolingual English texts. We also show that hierarchical k-means
clustering increases the similarity to the original taxonomy, when
compared with a bottom-up agglomerative clustering approach.