Industrial Memories: Exploring the Findings of Government Inquiries with Neural Word Embedding and Machine Learning [chapter]

Susan Leavy, Emilie Pine, Mark T. Keane
2019 Lecture Notes in Computer Science  
Series þÿ E u r o p e a n C o n f e r e n c e , E C M L P K D D 2 0 1 8 , D u b l i n , I r e l a n d , S e p t e m b e r 1 0 1 4 , 2 0 1 8 , Proceedings, Part III Publisher ECML-PKDD Link to online version Abstract. We present a text mining system to support the exploration of large volumes of text detailing the findings of government inquiries. Despite their historical significance and potential societal impact, key findings of inquiries are often hidden within lengthy documents and remain
more » ... ccessible to the general public. We transform the findings of the Irish government's inquiry into industrial schools and through the use of word embedding, text classification and visualization, present an interactive web-based platform that enables the exploration of the text in new ways to uncover new historical insights.
doi:10.1007/978-3-030-10997-4_52 fatcat:ebc2mbxa55ga7a35u3ypvbj34m