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Machine-Learning Algorithm Ranks the World's Most Notable Authors

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A look at how the new software ranks public domain works.

New software features an algorithm that automatically generates an independent ranking of notable authors for a given year.

Credit: Technology Review

Dartmouth College professor Allen Riddell has developed software that automatically ranks those authors and creators whose work has entered the public domain by how likely they are to be of interest to academics and the general public.

Riddell's public domain ranking tool uses a machine-learning algorithm to mine and analyze data from Wikipedia and the University of Pennsylvania's database of more than 1 million public domain books. The algorithm gathers data such as length and age from an author's Wikipedia entry and correlates it with the presence of a digital copy of their works in the Pennsylvania database to generate its ratings on the reasoning that authorities with lengthier and more active Wikipedia pages and existing digital copies of their works are more likely to be of interest.

Of those authors and personages whose works are entering the public domain in some areas of the world next year, Riddell ranks TS Eliot, Somerset Maugham, Winston Churchill, and Malcolm X the highest. The program also breaks its rankings out by category; for example, Jean-Paul Sartre is the top-ranked French philosopher in the public domain. Riddell acknowledges his algorithm, while independent of the biases of the committees often tasked with ranking artistic works, is still susceptible to biases of Wikipedia and its editors.

From Technology Review
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