Analyzing the quality of data prior to constructing data mining models is emerging as an important issue. Algorithms for identifying noise in a given data set can provide a good me...
Jason Van Hulse, Taghi M. Khoshgoftaar, Haiying Hu...
Background: Assessment of array quality is an essential step in the analysis of data from microarray experiments. Once detected, less reliable arrays are typically excluded or &qu...
Matthew E. Ritchie, Dileepa S. Diyagama, Jody Neil...
Background: Gene expression studies greatly contribute to our understanding of complex relationships in gene regulatory networks. However, the complexity of array design, producti...
Abstract— Improving data quality is a time-consuming, laborintensive and often domain specific operation. A recent principled approach for repairing dirty database is to use dat...
Mohamed Yakout, Ahmed K. Elmagarmid, Jennifer Nevi...
Improving data quality is a time-consuming, labor-intensive and often domain specific operation. Existing data repair approaches are either fully automated or not efficient in int...
Mohamed Yakout, Ahmed K. Elmagarmid, Jennifer Nevi...
Quality of data plays a very important role in any scientific research. In this paper we present some of the challenges that we face in managing and maintaining data quality for a...
Real-life date is often dirty and costs billions of pounds to businesses worldwide each year. This paper presents a promising approach to improving data quality. It effectively det...
Information, stored in databases, is a key competitive advantage of many companies. However, this importance does not imply that managers will view data as a strategic resource or...
Implementing a Total Data Quality Management (TDQM) program is not a trivial undertaking. Two key steps are (1) to clearly define what an organization means by data quality and (2...
What modes and domains of knowledge about data production processes are most critical for producing high-quality data? This study provides an answer to this question. Data are coll...