A Spectral Co-Clustering Approach for Dynamic Data

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Title: A Spectral Co-Clustering Approach for Dynamic Data
Authors: Greene, DerekCunningham, 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 dataData clustering algorithmsAnnotated 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Status of Item: Not peer reviewed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

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