Data cleaning: An abstraction-based approach

Koshley, Dileep Kumar; Halder, Raju

doi:10.1109/icacci.2015.7275695

Cited by 3 publications

(1 citation statement)

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“…Record linkage similarity measures algorithm: This technique is used to compare two relational tuples for their similarity. Koshley and Halder (2015) proposed an abstraction-based data cleaning approach that results in instances of abstract domains. Many errors enter in data like typo, measurement and data integration errors that are harmful during decision making and analysis.…”

Section: Token-based Data Cleaningmentioning

confidence: 99%

GeoWebCln: An Intensive Cleaning Architecture for Geospatial Metadata

Sheoran

Parmar

2022

Quaestiones Geographicae

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Developments in big data technology, wireless networks, Geographic information system (GIS) technology, and internet growth has increased the volume of data at an exponential rate. Internet users are generating data with every single click. Geospatial metadata is widely used for urban planning, map making, spatial data analysis, and so on. Scientific databases use metadata for computations and query processing. Cleaning of data is required for improving the quality of geospatial metadata for scientific computations and spatial data analysis. In this paper, we have designed a data cleaning tool named as GeoWebCln to remove useless data from geospatial metadata in a user-friendly environment using the Python console of QGIS Software.

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Section: Token-based Data Cleaningmentioning

confidence: 99%