A Spectral Co-Clustering Approach for Dynamic Data
|Title:||A Spectral Co-Clustering Approach for Dynamic Data||Authors:||Greene, Derek; Cunningham, Pádraig||Permanent link:||http://hdl.handle.net/10197/12401||Date:||Aug-2011||Online since:||2021-08-09T15:58:45Z||Abstract:||A common task in many domains with a temporal aspect involves identifying and tracking clusters over time. Often dynamic data will have a feature-based representation. In some cases, a direct mapping will exist for both objects and features over time. But in many scenarios, smaller subsets of objects or features alone will persist across successive time periods. To address this issue, we propose a dynamic spectral co-clustering algorithm for simultaneously clustering objects and features over time, as represented by a set of related bipartite graphs. We evaluate the algorithm on several synthetic datasets, a benchmark text corpus, and social bookmarking data.||Funding Details:||Science Foundation Ireland||Type of material:||Technical Report||Publisher:||University College Dublin. School of Computer Science and Informatics||Series/Report no.:||UCD CSI Technical Reports; ucd-csi-2011-08||Copyright (published version):||2011 the Authors||Keywords:||Dynamic data; Data clustering algorithms; Annotated corpora||Other versions:||https://web.archive.org/web/20080226040105/http:/csiweb.ucd.ie/Research/TechnicalReports.html||Language:||en||Status of Item:||Not peer reviewed||This item is made available under a Creative Commons License:||https://creativecommons.org/licenses/by-nc-nd/3.0/ie/|
|Appears in Collections:||CASL Research Collection|
Computer Science and Informatics Technical Reports
Show full item record
If you are a publisher or author and have copyright concerns for any item, please email firstname.lastname@example.org and the item will be withdrawn immediately. The author or person responsible for depositing the article will be contacted within one business day.