Scalable Content-Based Analysis of Images in Web Archives with TensorFlow and the Archives Unleashed Toolkit
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Date
2019
Authors
Yang, Hsiu-Wei
Liu, Linqing
Milligan, Ian
Ruest, Nick
Lin, Jimmy
Journal Title
Journal ISSN
Volume Title
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Abstract
We demonstrate the integration of the Archives Unleashed Toolkit, a scalable platform for exploring web archives, with Google's TensorFlow deep learning toolkit to provide scholars with content-based image analysis capabilities. By applying pretrained deep neural networks for object detection, we are able to extract images of common objects from a 4TB web archive of GeoCities, which we then compile into browsable collages. This case study illustrates the types of interesting analyses enabled by combining big data and deep learning capabilities.
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Keywords
TensorFlow, machine learning, image analysis, web archives, Apache Spark, PySpark
Citation
Hsiu-Wei Yang, Linqing Liu, Ian Milligan, Nick Ruest, and Jimmy Lin. “Scalable Content-Based Analysis of Images in Web Archives with TensorFlow and the Archives Unleashed Toolkit.” Proceedings of the ACM/IEEE Joint Conference on Digital Libraries, Vol. 19 (2019).
Hsiu-Wei Yang, Linqing Liu, Ian Milligan, Nick Ruest, and Jimmy Lin. “Scalable Content-Based Analysis of Images in Web Archives with TensorFlow and the Archives Unleashed Toolkit.” Proceedings of the ACM/IEEE Joint Conference on Digital Libraries, Vol. 19 (2019).
Hsiu-Wei Yang, Linqing Liu, Ian Milligan, Nick Ruest, and Jimmy Lin. “Scalable Content-Based Analysis of Images in Web Archives with TensorFlow and the Archives Unleashed Toolkit.” Proceedings of the ACM/IEEE Joint Conference on Digital Libraries, Vol. 19 (2019).