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Cleaning Data With Selection Rules
IEEE Access, 2022 In this paper, we propose and study a type of tuple-level constraint that arises from the selection operator $\sigma $ of relational algebra and that closely resembles the concepts of tuple-level denial constraints.
Toon Boeckling +2 more
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Continuous data cleaning [PDF]
2014 IEEE 30th International Conference on Data Engineering, 2014 In declarative data cleaning, data semantics are encoded as constraints and errors arise when the data violates the constraints. Various forms of statistical and logical inference can be used to reason about and repair inconsistencies (errors) in data. Recently, unified approaches that repair both errors in data and errors in semantics (the constraints)
Maksims Volkovs +3 more
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LR-BCA: Label Ranking for Bridge Condition Assessment
IEEE Access, 2021 Bridge condition assessment (BCA) plays an important role in modern bridge management. Existing assessment methods are time-consuming, labor-intensive and error-prone. The use of machine learning for BCA can effectively solve the above problems. However,
Kai Wang, Tong Ruan, Faxiang Xie
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Establishing a sorting protocol for healthcare databases
Journal of Public Health Research, 2021 Background: Health information records in many countries, especially developing countries, are still paper based. Compared to electronic systems, paper-based systems are disadvantageous in terms of data storage and data extraction.
Elie Ghabi +7 more
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Data, 2021 It is recognized that the performance of any prediction model is a function of several factors. One of the most significant factors is the adopted preprocessing techniques.
Esra’a Alshdaifat +4 more
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An extensible Framework for Data Cleaning [PDF]
Proceedings of 16th International Conference on Data Engineering (Cat. No.00CB37073), 2005 Data integration solutions dealing with large amounts of data have been strongly required in the last few years. Besides the traditional data integration problems (e.g. schema integration, local to global schema mappings), three additional data problems have to be dealt with: (1) the absence of universal keys across different databases that is known as
Galhardas, Helena +3 more
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Exploratory Data Mining and Data Cleaning
Journal of Statistical Software, 2004 s not available for ...
Nicholas Cox
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A Protocol for Collecting Burned Area Time Series Cross-Check Data
Fire, 2022 Data on wildfire growth are useful for multiple research purposes but are frequently unavailable and often have data quality problems. For these reasons, we developed a protocol for collecting daily burned area time series from the InciWeb website ...
Harry R. Podschwit +2 more
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Data Validation Infrastructure for R
Journal of Statistical Software, 2021 Checking data quality against domain knowledge is a common activity that pervades statistical analysis from raw data to output. The R package validate facilitates this task by capturing and applying expert knowledge in the form of validation rules ...
Mark P. J. van der Loo, Edwin de Jonge
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The VLDB Journal, 2019 Data cleaning (or data repairing) is considered a crucial problem in many database-related tasks. It consists in making a database consistent with respect to a given set of constraints. In recent years, repairing methods have been proposed for several classes of constraints.
Floris Geerts +3 more
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