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Text Mining in der elektronischen Postverteilung einer Bundesbehörde

Text Mining in der elektronischen Postverteilung einer Bundesbehörde

          
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About the Book

Masterarbeit aus dem Jahr 2018 im Fachbereich Informatik - Industrie 4.0, Note: 2,0, FOM Hochschule für Oekonomie & Management gemeinnützige GmbH, Frankfurt früher Fachhochschule (IT Management), Sprache: Deutsch, Abstract: Bisher unbekanntes Wissen aus unstrukturierten Texten zu extrahieren ist Ziel von Text Mining. Es wird oft als Methode, Verfahren, Konzept oder Werkzeug bezeichnet. In sogenannten unstrukturierten Texten stößt man auf bisher nicht bekannte Inhalte, die durch geeignete Methoden erforscht werden können. Das Nutzen dieser Methoden wird daher auch zu Maßnahmen des Wissensmanagements gefasst. Eine Statistik der International Data Corporation (IDC) besagt, dass Unternehmen weiterhin mit dem Wachstum von Daten mit unstrukturiertem Inhalt rechnen. Sie zählen zu den am stärksten wachsenden Datenquellen. In behördlichen Einrichtungen ist es nicht unüblich unstrukturierte Dokumente digital zu verwalten. Der Plan der Bundesregierung ist bis zum Jahr 2020 in allen Bundesverwaltungen Dokumente bzw. Akten in elektronischer Form zu führen. Die Optimierung von Verwaltungsabläufen ist im Rahmen dieser Digitalisierungsinitiative nicht nur sinnvoll, sondern gleichzeitig auch eine gesetzliche Vorgabe im Rahmen des E-Government-Gesetzes (EGovG). Man sollte an erster Stelle, an der Dokumente mit dem Unternehmen zusammentreffen, also der Poststelle, beginnen. So sagt auch Thomas Kleiner, CEO des Unternehmens iXenso, in einem Interview mit dem ECMguide: "Irrläufer und schlecht lesbare oder falsch interpretierte Dokumente sorgen nicht nur für Frust beim Empfänger, sondern verschlechtern auch die Qualität der Prozesse". Es wird deutlich, welche Bedeutung der Posteingang für ein Unternehmen hat. Gerade für Behörden, bei denen ein Tätigwerden oftmals nur durch Anträge oder Anfragen begründet wird, ist dieses Problem enorm. In dem Zusammenhang liest man immer wieder von Text Mining, das zur Lösung für automatisierte Postverteilung genutzt werden kann. Für die erfolg


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Product Details
  • ISBN-13: 9783668798243
  • Publisher: Grin Verlag
  • Publisher Imprint: Grin Verlag
  • Height: 210 mm
  • No of Pages: 164
  • Spine Width: 10 mm
  • Width: 148 mm
  • ISBN-10: 3668798249
  • Publisher Date: 05 Oct 2018
  • Binding: Paperback
  • Language: German
  • Returnable: N
  • Weight: 222 gr


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