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Editors’ Comments Where the JDIQ Articles Come From: Incubating Research in an Emerging Field
Stuart E. Madnick, Yang W. Lee
Article No.: 13
Towards a Method for Data Accuracy Assessment Utilizing a Bayesian Network Learning Algorithm
V. Sessions, M. Valtorta
Article No.: 14
This research develops a data quality algorithm entitled the Accuracy Assessment Algorithm (AAA). This is an extension of research in developing an enhancement to a Bayesian Network (BN) learning algorithm called the Data Quality (DQ) algorithm....
Dual Assessment of Data Quality in Customer Databases
Adir Even, G. Shankaranarayanan
Article No.: 15
Quantitative assessment of data quality is critical for identifying the presence of data defects and the extent of the damage due to these defects. Quantitative assessment can help define realistic quality improvement targets, track progress,...
An Accuracy Metric: Percentages, Randomness, and Probabilities
Craig W. Fisher, Eitel J. M. Lauria, Carolyn C. Matheus
Article No.: 16
Practitioners and researchers regularly refer to error rates or accuracy percentages of databases. The former is the number of cells in error divided by the total number of cells; the latter is the number of correct cells divided by the total...
Compensated Signature Embedding for Multimedia Content Authentication
Sufyan Ababneh, Rashid Ansari, Ashfaq Khokhar
Article No.: 17
One of the main goals of digital content authentication and preservation techniques is to guarantee the originality and quality of the information. In this article, robust watermarking is used to embed content-based fragile signatures in...