Clipping the Page – Automatic Article Detection and Marking Software in Production of Newspaper Clippings of a Digitized Historical Journalistic Collection

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http://hdl.handle.net/10138/310059

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Kettunen , K , Pääkkönen , T & Liukkonen , E S 2019 , Clipping the Page – Automatic Article Detection and Marking Software in Production of Newspaper Clippings of a Digitized Historical Journalistic Collection . in A Doucet , A Isaac , K Golub , T Aalberg & A Jatowt (eds) , Digital Libraries for Open Knowledge 23rd International Conference on Theory and Practice of Digital Libraries, TPDL 2019, Oslo, Norway, September 9-12, 2019, Proceedings . Lecture Notes in Computer Science , no. 11799 , Springer Nature Switzerland , Basel , pp. 356-60 , TPDL 2019 , 09/09/2019 . https://doi.org/10.1007/978-3-030-30760-8_33

Title: Clipping the Page – Automatic Article Detection and Marking Software in Production of Newspaper Clippings of a Digitized Historical Journalistic Collection
Author: Kettunen, Kimmo; Pääkkönen, Tuula; Liukkonen, Erno Samuli
Editor: Doucet, Antoine; Isaac, Antoine; Golub, Koraljka; Aalberg, Trond; Jatowt, Adam
Contributor: University of Helsinki, The National Library of Finland, Research Library
University of Helsinki, The National Library of Finland, Research Library
University of Helsinki, The National Library of Finland, Research Library
Publisher: Springer Nature Switzerland
Date: 2019-08-30
Language: eng
Number of pages: 5
Belongs to series: Digital Libraries for Open Knowledge 23rd International Conference on Theory and Practice of Digital Libraries, TPDL 2019, Oslo, Norway, September 9-12, 2019, Proceedings
Belongs to series: Lecture Notes in Computer Science
ISBN: 978-3-030-30759-2
978-3-030-30760-8
URI: http://hdl.handle.net/10138/310059
Abstract: This paper describes utilization of article detection and extraction on the Finnish Digi (https://digi.kansalliskirjasto.fi/etusivu?set_language=en) newspaper material of the National Library of Finland (NLF) using data of one newspaper, Uusi Suometar 1869–1918. We use PIVAJ software [1] for detection and marking of articles in our collection. Out of the separated articles we can produce automatic clippings for the user. The user can collect clippings for own use both as images and as OCRed text. Together these functionalities improve usability of the digitized journalistic collection by providing a structured access to the contents of a page.
Subject: 113 Computer and information sciences
518 Media and communications
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