Jorge Bernardino

Management Science and Operations Research · 2015

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Management Science and Operations Research — 8 citations into it
• Management Information Systems — 5 citations into it

Whom Jorge Bernardino trusts

Their strongest outbound trust, strongest first, inferred from their citations.

1. Diane M. Strong (in Management Information Systems)
2. Richard Y. Wang (in Management Information Systems)

Papers from Jorge Bernardino's perspective

Ordered by how strongly the researchers Jorge Bernardino trusts endorse each paper. Same corpus, a different order for every researcher.

1. Data Cleaning: Problems and Current Approaches.
2. AIMQ: a methodology for information quality assessment (Information Manager (The))
3. Data Quality: Concepts, Methodologies and Techniques
4. Information quality benchmarks: product and service performance (CACM)
5. Assessment Methods for Information Quality Criteria (IQ)
6. Methodologies for data quality assessment and improvement (CSUR)
7. A conceptual framework and belief‐function approach to assessing overall information quality (International Journal of Intelligent Systems)
8. Problems , Methods , and Challenges in Comprehensive Data Cleansing
9. Data quality for data science, predictive analytics, and big data in supply chain management: An introduction to the problem and suggestions for research and applications
10. A Taxonomy of Dirty Data

Their papers

• A Survey on Data Quality: Classifying Poor Data (2015) — 144 citations