Support for User Involvement in Data Cleaning

Galhardas, Héléna; Lopes, Antónia; Santos, Emanuel

doi:10.1007/978-3-642-23544-3_11

Cited by 11 publications

(4 citation statements)

References 11 publications

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“…Pre-processing is an important step that enhances the quality and produces an image in which minutiae can be detected correctly [2]. A data cleaning graph with data quality constraints is used to help users in identifying the points of the graph, and the records need the attention towards manual data repairs to represent the required feedback to clean data items manually [3]. In this paper, three major data mining methods, namely functional dependency mining, association rule mining and Bagging SVMs for data cleaning are discussed [4].…”

Section: A Back Groundmentioning

confidence: 99%

A Novel Approach for Image Recognition to Enhance the Quality of Decision Making by Applying Degree of Correlation Using Artificial Neural Networks

Dara¹,

Satyanarayana²,

Govardhan³

2014

IJIGSP

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Many diversified applications do exist in science & technology, which make use of the primary theory of a recognition phenomenon as one of its solutions. Recognition scenario is incorporated with a set of decisions and the action according to the decision purely relies on the quality of extracted information on utmost applications. Thus, the quality decision making absolutely reckons on processing momentum and precision which are entirely coupled with recognition methodology. In this article, a latest rule is formulated based on the degree of correlation to characterize the generalized recognition constraint and the application is explored with respect to image based information extraction. Machine learning based perception called feed forward architecture of Artificial Neural Network has been applied to attain the expected eminence of elucidation. The proposed method furnishes extraordinary advantages such as less memory requirements, extremely high level security for storing data, exceptional speed and gentle implementation approach.

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Section: A Back Groundmentioning

confidence: 99%

A Novel Approach for Image Recognition to Enhance the Quality of Decision Making by Applying Degree of Correlation Using Artificial Neural Networks

Dara¹,

Satyanarayana²,

Govardhan³

2014

IJIGSP

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“…By collecting the multi-platform information established by the administrative departments of health and family planning at all levels and the departments of politics, public security, civil affairs, human resources, social security, and the Disabled Persons’ Federation, data collection and analysis are carried out [ 13 , 14 ]. Classified according to risk factors.…”

Section: Design Of Early Warning Monitoring Modelmentioning

confidence: 99%

Research on Early Warning Monitoring Model of Serious Mental Disorder Based on Multi-source Heterogeneous Data Sources

Chen

Zhao

Zhong

et al. 2020

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Patients with severe mental disorders are sudden and aggressive, and the means may be more cruel. The data shows that the number of serious mental disorders is increasing. In order to prevent the occurrence of accidents and disasters in patients with mental illness, active intervention should be carried out to design an early warning and monitoring system for serious mental disorders. By collecting administrative departments of health and family planning at all levels, it is necessary to cooperate with the political and legal, public security, civil affairs, human resources, social security, and the Disabled Persons’ Federation. The established platform information is used to summarize multi-source heterogeneous data. Establish an early warning monitoring model, classify 10 risk factors from four levels, establish a risk factor assessment model, and set up different levels of treatment intervention programs. It is described from the perspectives of design ideas, design principles, and architecture design. The construction of an early warning and monitoring mechanism for serious mental disorders can effectively integrate the high-quality resources of mental health institutions at all levels, guide the rational allocation of resources, improve the management of serious mental disorders, detect the morbidity of patients with mental disorders early, and promptly intervene to reduce the risk of accidents.

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“…Examples in the e-commerce related area include DEXTER [13] and DI-ADEM [7] that parse e-commerce websites automatically to extract structured product data. There are also examples such as Wrangler [12] and user-involved data cleaning system [9] that leverage human feedback to construct data transformations. In this paper, schema auto generation is not our focus due to the limited scope of the system -it is designed to solve the internal needs of a common data model for one company, which is more suitable for manual design and update.…”

Section: Related Workmentioning

confidence: 99%

A Semantic Schema for Data Quality Management in a Multi-Tenant Data Platform

Zhou,

Esparza,

Garshol

2019

Preprint

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Schibsted Media Group is a global marketplace company with presence in more than 20 countries. It is undergoing a digital transformation to convert data silos to a multi-tenant system based on a common data platform. Good data quality based on a common schema on the semantic level is essential for building successful data-driven products across marketplaces. To solve this challenge, we developed the data quality tooling based on a semantic schema management system to support schema evolution with versioning, testing and transformation. It can monitor the data quality requirements for different applications and handle incoming data consisting of multiple schema versions. Today the system is operating in production and processes over one billion events per day for over 100 applications.

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Support for User Involvement in Data Cleaning

Cited by 11 publications

References 11 publications

A Novel Approach for Image Recognition to Enhance the Quality of Decision Making by Applying Degree of Correlation Using Artificial Neural Networks

A Novel Approach for Image Recognition to Enhance the Quality of Decision Making by Applying Degree of Correlation Using Artificial Neural Networks

Research on Early Warning Monitoring Model of Serious Mental Disorder Based on Multi-source Heterogeneous Data Sources

A Semantic Schema for Data Quality Management in a Multi-Tenant Data Platform

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