The Chamois Reconfigurable Data-Mining Architecture
| Autor: | Sang-Ho Lee, Min Soo Lee, Ho Sook Kim, Dong Sub Cho, Myung Hwa Kim, Wol Young Lee, Anmo Jeong, Ki Ho Lee, Meejeong Lee, Kijoon Chae, Won Ki Kim, Byoungju Choi, Jung-Won Lee, Hwan-Seung Yong, Seung Soo Park |
|---|---|
| Rok vydání: | 2002 |
| Předmět: |
Engineering
GeneralLiterature_INTRODUCTORYANDSURVEY business.industry Process (engineering) Suite InformationSystems_DATABASEMANAGEMENT computer.software_genre Data type Set (abstract data type) Software Knowledge extraction Component (UML) Data mining Architecture Software engineering business computer |
| Zdroj: | The Journal of Object Technology. 1:21 |
| ISSN: | 1660-1769 |
| DOI: | 10.5381/jot.2002.1.2.c2 |
| Popis: | The process of knowledge discovery in data (KDD) stored in computers in general requires iterations of three stages: data preparation, data mining, and results analysis. A variety of software tools are available for each of the stages. KDD environments, objectives of KDD, and types of data to be mined affect the choice of software tools in each stage. This article proposes a component-based architecture for an “end-to-end” integrated suite of KDD software tools that supports the entire KDD process. The architecture allows the configuring of an integrated tool suite with software tools appropriate for a given KDD environment and a given set of KDD objectives. The architecture is a part of the Chamois component-based knowledge-engineering framework under development at Ewha Women’s University in Korea. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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