AIDA: Intelligent image analysis to automatically detect poems in digital archives of historic newspapers

Leen Kiat Soh, Elizabeth Lorang, Yi Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We describe an intelligent image analysis approach to automatically detect poems in digitally archived historic newspapers. Our application, Image Analysis for Archival Discovery, or Aida, integrates computer vision to capture visual cues based on visual structures of poetic works'instead of the meaning or content'and machine learning to train an artificial neural network to determine whether an image has poetic text. We have tested our application on almost 17,000 image snippets and obtained promising accuracies, precision, and recall. The application is currently being deployed at two institutions for digital library and literary research.

Original languageEnglish (US)
Title of host publication32nd AAAI Conference on Artificial Intelligence, AAAI 2018
PublisherAAAI Press
Pages7837-7842
Number of pages6
ISBN (Electronic)9781577358008
Publication statusPublished - Jan 1 2018
Event32nd AAAI Conference on Artificial Intelligence, AAAI 2018 - New Orleans, United States
Duration: Feb 2 2018Feb 7 2018

Publication series

Name32nd AAAI Conference on Artificial Intelligence, AAAI 2018

Conference

Conference32nd AAAI Conference on Artificial Intelligence, AAAI 2018
CountryUnited States
CityNew Orleans
Period2/2/182/7/18

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ASJC Scopus subject areas

  • Artificial Intelligence

Cite this

Soh, L. K., Lorang, E., & Liu, Y. (2018). AIDA: Intelligent image analysis to automatically detect poems in digital archives of historic newspapers. In 32nd AAAI Conference on Artificial Intelligence, AAAI 2018 (pp. 7837-7842). (32nd AAAI Conference on Artificial Intelligence, AAAI 2018). AAAI Press.