IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

A Component-Based Data Management and Knowledge Discovery Framework for Aviation Studies

A Component-Based Data Management and Knowledge Discovery Framework for Aviation Studies
View Sample PDF
Author(s): M. Brian Blake (Georgetown University, USA), Lisa Singh (Georgetown University, USA), Andrew B. Williams (The MITRE Corporation, USA), Wendell Norman (Georgetown University, USA)and Amy L. Sliva (Spelman College, USA)
Copyright: 2009
Pages: 13
Source title: Selected Readings on Telecommunications and Networking
Source Author(s)/Editor(s): Jairo Gutierrez (University of Auckland, NZ)
DOI: 10.4018/978-1-60566-094-3.ch006

Purchase

View A Component-Based Data Management and Knowledge Discovery Framework for Aviation Studies on the publisher's website for pricing and purchasing information.

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. Since traditional transaction databases are not optimized for analytical processing, they 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.

Related Content

Raquel Sánchez Ruiz, Isabel López Cirugeda. © 2024. 22 pages.
Rocío Luque-González, Inmaculada Marín-López, Mercedes Gómez-López. © 2024. 22 pages.
Bima Sapkota, Xuwei Luo, Muna Sapkota, Murat Akarsu, Emmanuel Deogratias, Daphne Fauber, Rose Mbewe, Fidelis Mumba, Ram Krishna Panthi, Jill Newton, JoAnn Phillion. © 2024. 34 pages.
Karen Collett, Alina Slapac, Sarah A. Coppersmith, Jingxin Cheng. © 2024. 29 pages.
Maria Ines Marino, Stephanie Tadal, Nurhayat Bilge. © 2024. 25 pages.
Jaqueline Naidoo, Noah Borrero. © 2024. 19 pages.
Crystal Machado, Tami Seifert. © 2024. 20 pages.
Body Bottom