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A model for quality guaranteed resource-aware stream mining

Research output: Contribution to conferencePaperpeer-review

Standard

A model for quality guaranteed resource-aware stream mining. / Karnstedt, M.; Franke, C.; Gaber, M.

2007. Paper presented at Proceedings of the International Workshop on Knowledge Discovery from Ubiquitous Data Streams (IWKDUDS07), in conjunction with ECML and PKDD 2007, Warsaw, Poland.

Research output: Contribution to conferencePaperpeer-review

Harvard

Karnstedt, M, Franke, C & Gaber, M 2007, 'A model for quality guaranteed resource-aware stream mining', Paper presented at Proceedings of the International Workshop on Knowledge Discovery from Ubiquitous Data Streams (IWKDUDS07), in conjunction with ECML and PKDD 2007, Warsaw, Poland, 17/09/07.

APA

Karnstedt, M., Franke, C., & Gaber, M. (2007). A model for quality guaranteed resource-aware stream mining. Paper presented at Proceedings of the International Workshop on Knowledge Discovery from Ubiquitous Data Streams (IWKDUDS07), in conjunction with ECML and PKDD 2007, Warsaw, Poland.

Vancouver

Karnstedt M, Franke C, Gaber M. A model for quality guaranteed resource-aware stream mining. 2007. Paper presented at Proceedings of the International Workshop on Knowledge Discovery from Ubiquitous Data Streams (IWKDUDS07), in conjunction with ECML and PKDD 2007, Warsaw, Poland.

Author

Karnstedt, M. ; Franke, C. ; Gaber, M. / A model for quality guaranteed resource-aware stream mining. Paper presented at Proceedings of the International Workshop on Knowledge Discovery from Ubiquitous Data Streams (IWKDUDS07), in conjunction with ECML and PKDD 2007, Warsaw, Poland.

Bibtex

@conference{8d6f186db7c24f76a9a97da97d9ec6b5,
title = "A model for quality guaranteed resource-aware stream mining",
abstract = "Data streams are produced continuously at a high speed. Most data stream mining techniques address this challenge by using adaptation and approximation techniques. Adapting to available resources has been addressed recently. Although these techniques ensure the continuity of the data mining process under resource limitation, the quality of the output is still an open issue. In this paper, we propose a generic model that guarantees the quality of the output while maintaining efficient resource consumption. The model works on estimating the quality of the output given the available resources. Only a subset of these resources will be used that guarantees the minimum quality loss. The model is generalized for any data stream mining technique.",
author = "M. Karnstedt and C. Franke and M. Gaber",
year = "2007",
month = sep,
day = "17",
language = "English",
note = "Proceedings of the International Workshop on Knowledge Discovery from Ubiquitous Data Streams (IWKDUDS07), in conjunction with ECML and PKDD 2007 ; Conference date: 17-09-2007",

}

RIS

TY - CONF

T1 - A model for quality guaranteed resource-aware stream mining

AU - Karnstedt, M.

AU - Franke, C.

AU - Gaber, M.

PY - 2007/9/17

Y1 - 2007/9/17

N2 - Data streams are produced continuously at a high speed. Most data stream mining techniques address this challenge by using adaptation and approximation techniques. Adapting to available resources has been addressed recently. Although these techniques ensure the continuity of the data mining process under resource limitation, the quality of the output is still an open issue. In this paper, we propose a generic model that guarantees the quality of the output while maintaining efficient resource consumption. The model works on estimating the quality of the output given the available resources. Only a subset of these resources will be used that guarantees the minimum quality loss. The model is generalized for any data stream mining technique.

AB - Data streams are produced continuously at a high speed. Most data stream mining techniques address this challenge by using adaptation and approximation techniques. Adapting to available resources has been addressed recently. Although these techniques ensure the continuity of the data mining process under resource limitation, the quality of the output is still an open issue. In this paper, we propose a generic model that guarantees the quality of the output while maintaining efficient resource consumption. The model works on estimating the quality of the output given the available resources. Only a subset of these resources will be used that guarantees the minimum quality loss. The model is generalized for any data stream mining technique.

M3 - Paper

T2 - Proceedings of the International Workshop on Knowledge Discovery from Ubiquitous Data Streams (IWKDUDS07), in conjunction with ECML and PKDD 2007

Y2 - 17 September 2007

ER -

ID: 76337