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Sauer, C.S.: Analyse von Webcommunities und Extraktion von Wissen aus Communitydaten für Case-Based Reasoning Systeme (2010)
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- 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.
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Mazzucchelli, A.; Sartori , F.: String similarity in CBR platforms : a preliminary study (2014)
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- Pages
- S.22-29
- Source
- Metadata and semantics research: 8th Research Conference, MTSR 2014, Karlsruhe, Germany, November 27-29, 2014, Proceedings. Eds.: S. Closs et al
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Akerele, O.; David, A.; Osofisan, A.: Using the concepts of Case Based Reasoning and Basic Categories for enhancing adaptation to the user's level of knowledge in Decision Support System (2014)
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- Source
- Knowledge organization in the 21st century: between historical patterns and future prospects. Proceedings of the Thirteenth International ISKO Conference 19-22 May 2014, Kraków, Poland. Ed.: Wieslaw Babik
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He, W.; Tian, X.: ¬A longitudinal study of user queries and browsing requests in a case-based reasoning retrieval system (2017)
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- Abstract
- This article reports on a longitudinal analysis of query logs of a web-based case library system during an 8-year period (from 2005 to 2012). The analysis studies 3 different information-seeking approaches: keyword searching, browsing, and case-based reasoning (CBR) searching provided by the system by examining the query logs that stretch over 8 years. The longitudinal dimension of this study offers unique possibilities to see how users used the 3 different approaches over time. Various user information-seeking patterns and trends are identified through the query usage pattern analysis and session analysis. The study identified different user groups and found that a majority of the users tend to stick to their favorite information-seeking approach to meet their immediate information needs and do not seem to care whether alternative search options will offer greater benefits. The study also found that return users used CBR searching much more frequently than 1-time users and tend to use more query terms to look for information than 1-time users.
