Recurrent concepts in data streams classification
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F13%3A00068485" target="_blank" >RIV/00216224:14330/13:00068485 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/s10115-013-0654-6" target="_blank" >http://dx.doi.org/10.1007/s10115-013-0654-6</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s10115-013-0654-6" target="_blank" >10.1007/s10115-013-0654-6</a>
Alternative languages
Result language
angličtina
Original language name
Recurrent concepts in data streams classification
Original language description
This work addresses the problem of mining data streams generated in dynamic environments where the distribution underlying the observations may change over time. We present a system that monitors the evolution of the learning process. The system is ableto self-diagnose degradations of this process, using change detection mechanisms, and self-repair the decision models. The system uses meta-learning techniques that characterize the domain of applicability of previously learned models. The meta-learner can detect recurrence of contexts, using unlabeled examples, and take pro-active actions by activating previously learned models. The experimental evaluation on three text mining problems demonstrates the main advantages of the proposed system: it provides information about the recurrence of concepts and rapidly adapts decision models when drift occurs.
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/LG13010" target="_blank" >LG13010: Czech Republic representation in the European Research Consortium for Informatics and Mathematics (ERCIM)</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Knowledge and Information Systems
ISSN
0219-1377
e-ISSN
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Volume of the periodical
roč. 2013
Issue of the periodical within the volume
May
Country of publishing house
GB - UNITED KINGDOM
Number of pages
19
Pages from-to
1-19
UT code for WoS article
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EID of the result in the Scopus database
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