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Conference papers
Document stream clustering: experimenting an incremental algorithm and AR-based tools for highlighting dynamic trends.
Abstract : We address here two major challenges presented by dynamic data mining: 1) the stability challenge: we have implemented a rigorous incremental density-based clustering algorithm, independent from any initial conditions and ordering of the data-vectors stream, 2) the cognitive challenge: we have implemented a stringent selection process of association rules between clusters at time t-1 and time t for directly generating the main conclusions about the dynamics of a data-stream. We illustrate these points with an application to a two years and 2600 documents scientific information database.
Cited literature [25 references]
https://hal.archives-ouvertes.fr/hal-00336175
Contributor : Patricia Gautier <>
Submitted on : Monday, November 3, 2008 - 10:11:01 AM
Last modification on : Friday, April 2, 2021 - 3:38:53 AM
Long-term archiving on: : Monday, June 7, 2010 - 6:53:15 PM
Contributor : Patricia Gautier <>
Submitted on : Monday, November 3, 2008 - 10:11:01 AM
Last modification on : Friday, April 2, 2021 - 3:38:53 AM
Long-term archiving on: : Monday, June 7, 2010 - 6:53:15 PM
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Collnet_AL-MC-PC.pdf
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