NDLI: Toward Domain-Driven Data Mining

Content Provider	IEEE Xplore Digital Library
Author	Zhengxiang Zhu Jifa Gu Wenxin Yang Xingsen Li
Copyright Year	2008
Description	Author affiliation: Manage. Sch., Zhejiang Univ., Ningbo (Xingsen Li) \|\| Inst. of Syst. Eng., Dalian Univ. of Technol., Dalian (Zhengxiang Zhu) \|\| Dept. One, Chem. Defence Inst. of The PLA, Beijing (Wenxin Yang) \|\| Inst. of Syst. Sci., Chinese Acad. of Sci., Beijing (Jifa Gu)
Abstract	Traditional data mining is a data-driven trial-an-error process. It stops at discovered pattern/rule, either views data mining as an autonomous process, or only analyzes the issues in an isolated and case-by-case manner. As a result, the knowledge discovered is not interesting and actionable to constrained business. However, in many real world data mining tasks, for instance financial data mining in capital markets are highly constraint-based and domain- oriented. This paper proposes a new methodology named domain-driven data mining (DDDM), aims to discovery interesting and actionable knowledge for real user needs, overcome the gap between academia and business. DDDM integrates domain knowledge, expert experience, user interestingness, rule action ability and data into mining system. In this paper, A few basic concepts and methodologies are introduced firstly, after that the architecture is proposed and working detail is addressed. Finally, we specify issues that are either not addressed or insufficiently suited yet.
Starting Page	44
Ending Page	48
File Size	292286
Page Count	5
File Format	PDF
ISBN	9780769535050
DOI	10.1109/IITA.Workshops.2008.24
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-12-21
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	data mining Data engineering knowledge discovery Data mining Information technology actionability constrain Computer science Technology management Engineering management interestingness Programmable logic arrays Isolation technology Systems engineering and theory domain-driven Pattern analysis
Content Type	Text
Resource Type	Article

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