Please join us for an upcoming talk.
Lunch will be provided by Yahoo!
Ontology Learning by Supervised Hierarchical Clustering
Who: Grace, Hui Yang
When: Friday, May 16th, 12:00pm
Where: NSH 3002
This work makes novel use of supervised clustering as the basic
framework to construct concept ontology interactively or
automatically. Supervised hierarchical clustering is used to
organize ontology fragments, which are identified by techniques in
natural language processing and information retrieval, into
hierarchies. At each clustering iteration, a distance metric is
learned from the clustering given by either pseudo or real
feedback. K-medoids clustering with sampling is then used to group
the concepts at the higher level. A web-based cluster naming
algorithm is also presented. By conducting a user evaluation, the
system is shown to be effective to save human efforts in the
interactive runs. Both automatic and interactive runs of the
experiments show that the approach is effective.