License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/DagSemProc.07181.9
URN: urn:nbn:de:0030-drops-12617
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2007/1261/
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Höppner, Frank ;
Böttcher, Mirko
Reliably Capture Local Clusters in Noisy Domains From Parallel Universes
Abstract
When seeking for small local patterns it is very intricate to
distinguish between incidental agglomeration of noisy points and true
local patterns. We propose a new approach that
addresses this problem by exploiting temporal information which is
contained in most business data sets. The algorithm enables the
detection of local patterns in noisy data sets more reliable compared
to the case when the temporal information is ignored. This is achieved
by making use of the fact that noise does not reproduce its incidental
structure but even small patterns do. In particular, we developed a
method to track clusters over time based on an optimal match of data
partitions between time periods.
BibTeX - Entry
@InProceedings{hoppner_et_al:DagSemProc.07181.9,
author = {H\"{o}ppner, Frank and B\"{o}ttcher, Mirko},
title = {{Reliably Capture Local Clusters in Noisy Domains From Parallel Universes}},
booktitle = {Parallel Universes and Local Patterns},
pages = {1--2},
series = {Dagstuhl Seminar Proceedings (DagSemProc)},
ISSN = {1862-4405},
year = {2007},
volume = {7181},
editor = {Michael R. Berthold and Katharina Morik and Arno Siebes},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/opus/volltexte/2007/1261},
URN = {urn:nbn:de:0030-drops-12617},
doi = {10.4230/DagSemProc.07181.9},
annote = {Keywords: Local pattern, time, parallel universe}
}
Keywords: |
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Local pattern, time, parallel universe |
Collection: |
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07181 - Parallel Universes and Local Patterns |
Issue Date: |
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2007 |
Date of publication: |
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11.12.2007 |