In late February 2023, the Leddy Library’s Academic Data Centre at the University of Windsor hosted a workshop series called RDM & TDM in JupyterHub with Newspapers. TDM is an acronym for Text Data Mining (TDM) and one increasingly common approach to TDM highlighted in the workshop is the use of Optical Character Recognition (OCR) from newspapers for text processing. The imagery for several of the newspaper titles used for the workshop was improved to raise the OCR accuracy levels to better serve TDM technologies.
|First observed with the Feb. 4, 1892 edition of the Comber Herald, initial tests with Topaz suggested a 20% improvement in OCR accuracy. This past year has seen the entire collection reprocessed, which allowed the Herald to be included in the corpus for a TDM workshop held at the Leddy Library.|
|Another sample from 2021, this time the Sept. 22, 1971 edition of the Essex Times. Like the Herald, the Times was completely processed this past year with Topaz.|
The series was funded with a grant from Compute Ontario and showcased OurDigitalWorld’s extensive history with newspaper digitization, as well as its long-standing partnership with the University of Windsor. The growing interest in TDM among Ontario libraries was further confirmed by a Colloquium on TDM in Libraries event held at the University of Toronto in early May 2023. The use of newspapers for TDM was a major theme for the colloquium and a common strategy was identified where newspaper collections become substantial data assets for text processing.
ODW collections not only formed the basis of the Windsor workshop series, a subsequent data challenge using the newspaper collection was launched in March, which featured a collaboration with Hackforge, and a kick-off event at the LaSalle public library in partnership with the Essex County Library System. The Compute Ontario grant that supported these activities also provided funding for two graduate students, Akram Vasighizaker and Sumaiya Deen Muhammad, to carry out original research and the results are publicly available on the workshop github site.
TDM is an exciting new direction for newspaper digitization and represents a convergence between recent advances in artificial intelligence (AI) and machine learning with what is frequently the most extensive record of a community’s past, the local newspaper. Unique insights into the past and identifying trends and patterns are enhanced with the power of TDM and digitized newspapers, and it is hoped that ODW can continue to help libraries contribute to this promising area of research.
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