The Annotator: Difference between revisions
From Algolit
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The annotator asks for the guidance of the visitor in annotating the archive of Mundaneum. | The annotator asks for the guidance of the visitor in annotating the archive of Mundaneum. | ||
| − | The annotation process is a crucial step in supervised machine learning where the algorithm is given examples of what it needs to learn. A spam filter in training will be fed examples of spam and real messages. These examples are entries, or rows from the dataset with a label | + | The annotation process is a crucial step in supervised machine learning where the algorithm is given examples of what it needs to learn. A spam filter in training will be fed examples of spam and real messages. These examples are entries, or rows from the dataset with a label, spam or not-spam. |
| − | In this interface we ask you to help us classify the cleaned | + | In this process humans label or classify entries of the dataset. Once enough samples of each label have been gathered in the dataset, the computer can start the learning process. |
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| + | In this interface we ask you to help us classify the cleaned texts from the Mundaneum archive to expand our training set and improve the quality of the installation 'Classifying the World' in Oracles. | ||
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Concept, code, interface: Gijs de Heij | Concept, code, interface: Gijs de Heij | ||
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[[Category:Data_Workers]][[Category:Data_Workers_EN]] | [[Category:Data_Workers]][[Category:Data_Workers_EN]] | ||
Revision as of 18:36, 2 March 2019
by Algolit
The annotator asks for the guidance of the visitor in annotating the archive of Mundaneum.
The annotation process is a crucial step in supervised machine learning where the algorithm is given examples of what it needs to learn. A spam filter in training will be fed examples of spam and real messages. These examples are entries, or rows from the dataset with a label, spam or not-spam.
In this process humans label or classify entries of the dataset. Once enough samples of each label have been gathered in the dataset, the computer can start the learning process.
In this interface we ask you to help us classify the cleaned texts from the Mundaneum archive to expand our training set and improve the quality of the installation 'Classifying the World' in Oracles.
Concept, code, interface: Gijs de Heij