Sciweavers

KAIS
2007
112views more  KAIS 2007»
13 years 4 months ago
The pairwise attribute noise detection algorithm
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...
BMCBI
2006
100views more  BMCBI 2006»
13 years 4 months ago
Empirical array quality weights in the analysis of microarray data
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...
BMCBI
2010
136views more  BMCBI 2010»
13 years 4 months ago
The IronChip evaluation package: a package of perl modules for robust analysis of custom microarrays
Background: Gene expression studies greatly contribute to our understanding of complex relationships in gene regulatory networks. However, the complexity of array design, producti...
Yevhen Vainshtein, Mayka Sanchez, Alvis Brazma, Ma...
ICDE
2010
IEEE
266views Database» more  ICDE 2010»
13 years 4 months ago
Ranking for data repairs
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...
SIGMOD
2010
ACM
224views Database» more  SIGMOD 2010»
13 years 4 months ago
GDR: a system for guided data repair
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...
HPDC
2010
IEEE
13 years 5 months ago
Towards long term data quality in a large scale biometrics experiment
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...
Hoang Bui, Diane Wright, Clarence Helm, Rachel Wit...
BNCOD
2009
182views Database» more  BNCOD 2009»
13 years 5 months ago
Conditional Dependencies: A Principled Approach to Improving Data Quality
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...
Wenfei Fan, Floris Geerts, Xibei Jia
IQ
1996
13 years 5 months ago
Data Quality in Practice: Experience from the Front Line
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...
Christopher P. Firth
IQ
1997
13 years 5 months ago
Total Data Quality Management: The Case of IRI
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...
Rita Kovac, Yang W. Lee, Leo Pipino
IQ
2003
13 years 5 months ago
Process Knowledge and Data Quality Outcomes
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...
Yang W. Lee, Diane M. Strong