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Reassessing Data Quality for Information Products
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/3-540-33173-5openalex-snapshot
Data Quality : Concepts, Methodologies and Techniques
inferredcites →https://doi.org/10.1145/1541880.1541883openalex-snapshot
Methodologies for data quality assessment and improvement
inferredcites →https://doi.org/10.1287/mnsc.1040.0237openalex-snapshot
Assessing Data Quality for Information Products: Impact of Selection, Projection, and Cartesian Product
inferredcites →https://doi.org/10.5555/352925.352970openalex-snapshot
Assessing data quality for information products
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/qre.3692openalex-snapshot
Data Asset Quality Evaluation Framework Based on a Hybrid Multi‐Criteria Decision‐Making Method
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Efficient Twitter Data Cleansing Model for Data Analysis of the Pandemic Tweets
inferred← citeshttps://doi.org/10.1007/978-981-99-6101-6_22openalex-snapshot
The Role of Artificial Intelligence in Brand Building: A Review
inferred← citeshttps://doi.org/10.1007/s10796-019-09963-5openalex-snapshot
Managing Data Quality of the Data Warehouse: A Chance-Constrained Programming Approach
inferred← citeshttps://doi.org/10.1007/s11804-023-00326-wopenalex-snapshot
A Practical Data Quality Assessment Method for Raw Data in Vessel Operations
inferred← citeshttps://doi.org/10.1016/j.ijinfomgt.2019.08.002openalex-snapshot
Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy
inferred← citeshttps://doi.org/10.1016/j.ijpe.2014.04.018openalex-snapshot
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
inferred← citeshttps://doi.org/10.1016/j.tre.2022.103012openalex-snapshot
Blockchain and third-party logistics for global supply chain operations: Stakeholders’ perspectives and decision roadmap
inferred← citeshttps://doi.org/10.1108/ijlm-06-2017-0175openalex-snapshot
The influence of the Digital Divide on Big Data generation within supply chain management
inferred← citeshttps://doi.org/10.1108/md-06-2018-0669openalex-snapshot
Challenges with big data analytics in service supply chains in the UAE
inferred← citeshttps://doi.org/10.1109/fie.2018.8658588openalex-snapshot
Applying Product Manufacturing Techniques to Teach Data Analytics in Industrial Engineering: A Project Based Learning Experience
inferred← citeshttps://doi.org/10.1111/dsji.12274openalex-snapshot
Teaching binary logistic regression modeling in an introductory business analytics course
inferred← citeshttps://doi.org/10.1111/poms.13272openalex-snapshot
Efficient Detection of Environmental Violators: A Big Data Approach
inferred← citeshttps://doi.org/10.11591/ijece.v12i2.pp2001-2013openalex-snapshot
Automatic missing value imputation for cleaning phase of diabetic’s readmission prediction model
inferred← citeshttps://doi.org/10.11591/ijece.v12i6.pp5808-5820openalex-snapshot
Anomalies detection for smart-home energy forecasting using moving average
inferred← citeshttps://doi.org/10.1287/opre.1120.1128openalex-snapshot
Data Quality of Query Results with Generalized Selection Conditions
inferred← citeshttps://doi.org/10.3390/computers10070089openalex-snapshot
Distributed Interoperable Records: The Key to Better Supply Chain Management
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