JPL Technical Report Server

Value, cost, and sharing : open issues in constrained clustering

Show simple item record

dc.contributor.author Wagstaff, Kiri L.
dc.date.accessioned 2007-06-13T16:42:50Z
dc.date.available 2007-06-13T16:42:50Z
dc.date.issued 2006-09-18
dc.identifier.citation 5th International Workshop on Knowledge Discovery in Inducative Databases (KDID'06), Berlin, Germany, September 18, 2006 en
dc.identifier.clearanceno 06-2844
dc.identifier.uri http://hdl.handle.net/2014/40255
dc.description.abstract Clustering is an important tool for data mining, since it can identify major patterns or trends without any supervision (labeled data). Over the past five years, semi-supervised (constrained) clustering methods have become very popular. These methods began with incorporating pairwise constraints and have developed into more general methods that can learn appropriate distance metrics. However, several important open questions have arisen about which constraints are most useful, how they can be actively acquired, and when and how they should be propagated to neighboring points. This position paper describes these open questions and suggests future directions for constrained clustering research. en
dc.description.sponsorship NASA/JPL en
dc.format.extent 126312 bytes
dc.format.mimetype application/pdf
dc.language.iso en_US en
dc.publisher Pasadena, CA : Jet Propulsion Laboratory, National Aeronautics and Space Administration, 2006. en
dc.subject clustering en
dc.subject constraints en
dc.title Value, cost, and sharing : open issues in constrained clustering en
dc.type Preprint en


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search


Browse

My Account