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Abstract

Das Thema dieser Bachelorarbeit ist die automatische Generierung von Notationen der Dewey-Dezimalklassifikation für Metadaten. Die Metadaten sind im Dublin-Core-Format und stammen vom Server für wissenschaftliche Schriften der Hochschule Hannover. Zu Beginn erfolgt eine allgemeine Einführung über die Methoden und Hauptanwendungsbereiche des automatischen Klassifizierens. Danach werden die Dewey-Dezimalklassifikation und der Prozess der Metadatengewinnung beschrieben. Der theoretische Teil endet mit der Beschreibung von zwei Projekten. In dem ersten Projekt wurde ebenfalls versucht Metadaten mit Notationen der Dewey-Dezimalklassifikation anzureichern. Das Ergebnis des zweiten Projekts ist eine Konkordanz zwischen der Schlagwortnormdatei und der Dewey-Dezimalklassifikation. Diese Konkordanz wurde im praktischen Teil dieser Arbeit dazu benutzt um automatisch Notationen der Dewey-Dezimalklassifikation zu vergeben.

Content

Vgl. unter: http://opus.bsz-bw.de/fhhv/volltexte/2012/397/pdf/Bachelorarbeit_final_Korrektur01.pdf. Bachelorarbeit, Hochschule Hannover, Fakultät III - Medien, Information und Design, Abteilung Information und Kommunikation, Studiengang Informationsmanagement

Imprint

Hannover : Hochschule Hannover, Fakultät III - Medien, Information und Design, Abteilung Information und Kommunikation

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Abstract

The following paper deals with an automatic text classification method which does not require training documents. For this method the German Subject Heading Authority File (SWD), provided by the linked data service of the German National Library is used. Recently the SWD was enriched with notations of the Dewey Decimal Classification (DDC). In consequence it became possible to utilize the subject headings as textual representations for the notations of the DDC. Basically, we we derive the classification of a text from the classification of the words in the text given by the thesaurus. The method was tested by classifying 3826 OAI-Records from 7 different repositories. Mean reciprocal rank and recall were chosen as evaluation measure. Direct comparison to a machine learning method has shown that this method is definitely competitive. Thus we can conclude that the enriched version of the SWD provides high quality information with a broad coverage for classification of German scientific articles.