Document (#39233)

Author
Sauer, C.S.
Title
Analyse von Webcommunities und Extraktion von Wissen aus Communitydaten für Case-Based Reasoning Systeme
Imprint
Hildesheim : Universität Hildesheim, Institut für Informatik
Year
2010
Pages
162 S
Abstract
Die vorliegende Arbeit befasst sich mit den Möglichkeiten der Informationsextraktion aus den Daten von Webcommunities und der Verwendung der extrahierten Informationen in Case-Based Reasoning- (CBR) Systemen. Im Rahmen der Arbeit wird auf die Entwicklung der Webcommunities im Zeitraum der letzten 30 Jahre eingegangen. Es wird eine Klassifikation der derzeitig anzutreffenden Webcommunities in verschiedene Kategorien von Webcommunities vorgenommen. Diese Klassifikation erfolgt hinsichtlich der Struktur, der technischen Mittel sowie der Interessen der Nutzer dieser Webcommunities. Aufbauend auf die vorgenommene Klassifikation von Webcommunities erfolgt eine Untersuchung der Eignung dieser Kategorien von Webcommunities zur Informationsextraktion im Kontext der Verwendung der extrahierten Informationen in CBR-Systemen. Im selben Kontext werden verschiedene Ansätze und Techniken der Informationsextraktion auf ihre Eignung zur Extraktion von Wissen speziell für die Wissenscontainer von CBR -Systeme geprüft. Aufbauend auf den dadurch gewonnenen Erkenntnissen wird, angelehnt an den Prozess der Knowledge Discovery in Databases, ein eigenes Prozessmodell der Wissensextraktion aus Webcommunities für CBR-Systeme entworfen. Im Zuge der näheren Betrachtung dieses Prozessmodells wird auf verschiedene, durch die beabsichtigte Verwendung der extrahierten Informationen in den vier Wissenscontainern des CBR bedingte, Anforderungen an NLP- sowie IE-Techniken, die zur Extraktion dieser Daten verwendet werden, eingegangen. Die in den theoretischen Betrachtungen erlangten Erkenntnisse werden dann dazu eingesetzt, eine Anwendung zur Informationsextraktion aus einer Webcommunity für ein CBR-System, in Form der Knowledge Extraction Workbench zu implementieren. Diese IEAnwendung arbeitet im Kontext des auf der SEASALT-Architektur aufbauenden Projektes docQuery. Die Realisierung dieser IE-Anwendung wird dokumentiert sowie die Extraktionsergebnisse der Anwendung hinsichtlich ihres Umfanges und ihrer Qualität evaluiert.
Content
Masterarbeit, Universität Hildesheim, Institut für Informatik, Bereich Intelligente Informationssysteme. Vgl.: https://www.uni-hildesheim.de/media/fb4/informatik/AG_ESS/Paper/Sauer/Master_thesis_Sauer.pdf.
Theme
Internet
Case Based Reasoning

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  5. Social History and Industrial Classification - SHIC : Sozialgeschichtliche und industrielle Klassifikation - Eine thematische Klassifikation für Museumssammlungen (1999) 0.33
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