TY - GEN
T1 - Multilingual evidence improves clustering-based taxonomy extraction
AU - Hjelm, Hans
AU - Buitelaar, Paul
N1 - Publisher Copyright:
© 2008 The authors and IOS Press. All rights reserved.
PY - 2008/6
Y1 - 2008/6
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/84988468257
U2 - 10.3233/978-1-58603-891-5-288
DO - 10.3233/978-1-58603-891-5-288
M3 - Conference Publication
AN - SCOPUS:84988468257
SN - 978158603891
T3 - Frontiers in Artificial Intelligence and Applications
SP - 288
EP - 292
BT - Frontiers in Artificial Intelligence and Applications
PB - IOS Press BV
T2 - 18th European Conference on Artificial Intelligence, ECAI 2008
Y2 - 21 July 2008 through 25 July 2008
ER -