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

Imprecise Data and the Data Mining Process

Imprecise Data and the Data Mining Process
View Sample PDF
Author(s): Marvin L. Brown (Grambling State University, USA)and John F. Kros (East Carolina University, USA)
Copyright: 2009
Pages: 7
Source title: Encyclopedia of Data Warehousing and Mining, Second Edition
Source Author(s)/Editor(s): John Wang (Montclair State University, USA)
DOI: 10.4018/978-1-60566-010-3.ch155

Purchase

View Imprecise Data and the Data Mining Process on the publisher's website for pricing and purchasing information.

Abstract

Missing or inconsistent data has been a pervasive problem in data analysis since the origin of data collection. The management of missing data in organizations has recently been addressed as more firms implement large-scale enterprise resource planning systems (see Vosburg & Kumar, 2001; Xu et al., 2002). The issue of missing data becomes an even more pervasive dilemma in the knowledge discovery process, in that as more data is collected, the higher the likelihood of missing data becomes. The objective of this research is to discuss imprecise data and the data mining process. The article begins with a background analysis, including a brief review of both seminal and current literature. The main thrust of the chapter focuses on reasons for data inconsistency along with definitions of various types of missing data. Future trends followed by concluding remarks complete the chapter.

Related Content

Girija Ramdas, Irfan Naufal Umar, Nurullizam Jamiat, Nurul Azni Mhd Alkasirah. © 2024. 18 pages.
Natalia Riapina. © 2024. 29 pages.
Xinyu Chen, Wan Ahmad Jaafar Wan Yahaya. © 2024. 21 pages.
Fatema Ahmed Wali, Zahra Tammam. © 2024. 24 pages.
Su Jiayuan, Zhang Jingru. © 2024. 26 pages.
Pua Shiau Chen. © 2024. 21 pages.
Minh Tung Tran, Thu Trinh Thi, Lan Duong Hoai. © 2024. 23 pages.
Body Bottom