Cleaning Collections Data Using OpenRefine
نویسندگان
چکیده
منابع مشابه
Using Misclassification Analysis for Data Cleaning
It is posted here for your personal use. No further distribution is permitted. Data cleaning is a pre-processing technique used in most data mining problems. The purpose of data cleaning is to remove noise, inconsistent data and errors in order to obtain a better and representative data set to develop a reliable prediction model. In most prediction model, unclean data could sometime affect the ...
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In most classification problems, sometimes in order to achieve better results, data cleaning is used as a preprocessing technique. The purpose of data cleaning is to remove noise, inconsistent data and errors in the training data. This should enable the use of a better and representative data set to develop a reliable classification model. In most classification models, unclean data could somet...
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The problem of data cleaning, which consists of removing inconsistencies and errors from original data sets, is well known in the area of decision support systems and data warehouses. However, for some applications, existing ETL (Extraction Transformation Loading) and data cleaning tools for writing data cleaning programs are insufficient. One important challenge with them is the design of a da...
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With the increasing amount of available data, turning raw data into actionable information is a requirement in every field. However, one bottleneck that impedes the process is data cleaning. Data analysts usually spend over half of their time cleaning data that is dirty — inconsistent, inaccurate, missing, and so on — before they even begin to do any real analysis. It is a time consuming and co...
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ژورنال
عنوان ژورنال: Issues in Science and Technology Librarianship
سال: 2019
ISSN: 1092-1206
DOI: 10.29173/istl30