Abstract
Organizations are beginning to apply data mining and knowledge discovery techniques to their corporate data sets, thereby enabling the identification of trends and the discovery of inductive knowledge. Many times, traditional transactional databases are not optimized for analytical processing and must be transformed. This article proposes the use of modular components to decrease the overall amount of human processing and intervention necessary for the transformation process. Our approach configures components to extract data-sets using a set of "extraction hints". Our framework incorporates decentralized, generic components that are reusable across domains and databases. Finally, we detail an implementation of our component-based framework for an aviation data set.
| Original language | English |
|---|---|
| Title of host publication | Integrated Approaches in Information Technology and Web Engineering: Advancing Organizational Knowledge Sharing |
| Publisher | IGI Global |
| Pages | 244-256 |
| Number of pages | 13 |
| ISBN (Print) | 9781605664187 |
| DOIs | |
| State | Published - Dec 1 2008 |
| Externally published | Yes |
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ASJC Scopus subject areas
- Computer Science(all)
Cite this
Experience report : A component-based data management and knowledge discovery framework for aviation studies. / Blake, M. Brian; Singh, Lisa; Williams, Andrew B.; Norman, Wendell; Sliva, Amy L.
Integrated Approaches in Information Technology and Web Engineering: Advancing Organizational Knowledge Sharing. IGI Global, 2008. p. 244-256.Research output: Chapter in Book/Report/Conference proceeding › Chapter
}
TY - CHAP
T1 - Experience report
T2 - A component-based data management and knowledge discovery framework for aviation studies
AU - Blake, M. Brian
AU - Singh, Lisa
AU - Williams, Andrew B.
AU - Norman, Wendell
AU - Sliva, Amy L.
PY - 2008/12/1
Y1 - 2008/12/1
N2 - Organizations are beginning to apply data mining and knowledge discovery techniques to their corporate data sets, thereby enabling the identification of trends and the discovery of inductive knowledge. Many times, traditional transactional databases are not optimized for analytical processing and must be transformed. This article proposes the use of modular components to decrease the overall amount of human processing and intervention necessary for the transformation process. Our approach configures components to extract data-sets using a set of "extraction hints". Our framework incorporates decentralized, generic components that are reusable across domains and databases. Finally, we detail an implementation of our component-based framework for an aviation data set.
AB - Organizations are beginning to apply data mining and knowledge discovery techniques to their corporate data sets, thereby enabling the identification of trends and the discovery of inductive knowledge. Many times, traditional transactional databases are not optimized for analytical processing and must be transformed. This article proposes the use of modular components to decrease the overall amount of human processing and intervention necessary for the transformation process. Our approach configures components to extract data-sets using a set of "extraction hints". Our framework incorporates decentralized, generic components that are reusable across domains and databases. Finally, we detail an implementation of our component-based framework for an aviation data set.
UR - http://www.scopus.com/inward/record.url?scp=84901551098&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84901551098&partnerID=8YFLogxK
U2 - 10.4018/978-1-60566-418-7.ch016
DO - 10.4018/978-1-60566-418-7.ch016
M3 - Chapter
AN - SCOPUS:84901551098
SN - 9781605664187
SP - 244
EP - 256
BT - Integrated Approaches in Information Technology and Web Engineering: Advancing Organizational Knowledge Sharing
PB - IGI Global
ER -