Incremental learning optimization on knowledge discovery in dynamic business intelligent systems

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Incremental learning optimization on knowledge discovery in dynamic business intelligent systems. / Liu, Dun; Li, Tianrui; Ruan, Da; Zhang, Junbo.

In: Journal of Global Optimization, Vol. 51, 2011, p. 325-344.

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Liu, Dun ; Li, Tianrui ; Ruan, Da ; Zhang, Junbo. / Incremental learning optimization on knowledge discovery in dynamic business intelligent systems. In: Journal of Global Optimization. 2011 ; Vol. 51. pp. 325-344.

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@article{92ed061f8eb44aa09efe462216dcb70d,
title = "Incremental learning optimization on knowledge discovery in dynamic business intelligent systems",
abstract = "As business information quickly varies with time, the extraction of knowledge from the related dynamically changing database is vital for business decision making. For an incremental learning optimization on knowledge discovery, a new incremental matrix describes the changes of the system. An optimization incremental algorithm induces interesting knowledge when the object set varies over time. Experimental results validate the feasibility of the incremental learning optimization.",
keywords = "Rough set theory, Incremental learning, Accuracy, Coverage, Interesting knowledge, Business information, Optimization",
author = "Dun Liu and Tianrui Li and Da Ruan and Junbo Zhang",
note = "Score=10",
year = "2011",
doi = "10.1007/s10898-010-9607-8",
language = "English",
volume = "51",
pages = "325--344",
journal = "Journal of Global Optimization",
issn = "0925-5001",
publisher = "Springer",

}

RIS - Download

TY - JOUR

T1 - Incremental learning optimization on knowledge discovery in dynamic business intelligent systems

AU - Liu, Dun

AU - Li, Tianrui

AU - Ruan, Da

AU - Zhang, Junbo

N1 - Score=10

PY - 2011

Y1 - 2011

N2 - As business information quickly varies with time, the extraction of knowledge from the related dynamically changing database is vital for business decision making. For an incremental learning optimization on knowledge discovery, a new incremental matrix describes the changes of the system. An optimization incremental algorithm induces interesting knowledge when the object set varies over time. Experimental results validate the feasibility of the incremental learning optimization.

AB - As business information quickly varies with time, the extraction of knowledge from the related dynamically changing database is vital for business decision making. For an incremental learning optimization on knowledge discovery, a new incremental matrix describes the changes of the system. An optimization incremental algorithm induces interesting knowledge when the object set varies over time. Experimental results validate the feasibility of the incremental learning optimization.

KW - Rough set theory

KW - Incremental learning

KW - Accuracy

KW - Coverage

KW - Interesting knowledge

KW - Business information

KW - Optimization

UR - https://ecm.sckcen.be/OTCS/llisapi.dll/overview/39155148

U2 - 10.1007/s10898-010-9607-8

DO - 10.1007/s10898-010-9607-8

M3 - Article

VL - 51

SP - 325

EP - 344

JO - Journal of Global Optimization

JF - Journal of Global Optimization

SN - 0925-5001

ER -

ID: 6871796