Document stream clustering: experimenting an incremental algorithm and AR-based tools for highlighting dynamic trends

Details Document stream clustering: experimenting an incremental algorithm and AR-based tools for highlighting dynamic trends Document stream clustering: experimenting an incremental algorithm and AR-based tools for highlighting dynamic trends

2008-11-03

arxiv.org/abs/0811.0340v1

International Workshop on Webometrics, Informetrics and Scientometrics & Seventh COLLNET Meeting, France (2006)

Computer Science

Artificial Intelligence

Scientific paper

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.

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