Document (#37127)

Author
Witschel, H.F.
Title
Text, Wörter, Morpheme : Möglichkeiten einer automatischen Terminologie-Extraktion
Imprint
Leipzig : Universität / Fakultät für Mathematik und Informatik Institut für Informatik
Year
2004
Pages
141 S
Abstract
Die vorliegende Arbeit beschäftigt sich mit einem Teilgebiet des TextMining, versucht also Information (in diesem Fall Fachterminologie) aus natürlichsprachlichem Text zu extrahieren. Die der Arbeit zugrundeliegende These besagt, daß in vielen Gebieten des Text Mining die Kombination verschiedener Methoden sinnvoll sein kann, um dem Facettenreichtum natürlicher Sprache gerecht zu werden. Die bei der Terminologie-Extraktion angewandten Methoden sind statistischer und linguistischer (bzw. musterbasierter) Natur. Um sie herzuleiten, wurden einige Eigenschaften von Fachtermini herausgearbeitet, die für deren Extraktion relevant sind. So läßt sich z.B. die Tatsache, daß viele Fachbegriffe Nominalphrasen einer bestimmten Form sind, direkt für eine Suche nach gewissen POS-Mustern ausnützen, die Verteilung von Termen in Fachtexten führte zu einem statistischen Ansatz - der Differenzanalyse. Zusammen mit einigen weiteren wurden diese Ansätze in ein Verfahren integriert, welches in der Lage ist, aus dem Feedback eines Anwenders zu lernen und in mehreren Schritten die Suche nach Terminologie zu verfeinern. Dabei wurden mehrere Parameter des Verfahrens veränderlich belassen, d.h. der Anwender kann sie beliebig anpassen. Bei der Untersuchung der Ergebnisse anhand von zwei Fachtexten aus unterschiedlichen Domänen wurde deutlich, daß sich zwar die verschiedenen Verfahren gut ergänzen, daß aber die optimalen Werte der veränderbaren Parameter, ja selbst die Auswahl der angewendeten Verfahren text- und domänenabhängig sind.
Theme
Computerlinguistik
Data Mining

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