-
Hoang, H.H.; Tjoa, A.M: ¬The state of the art of ontology-based query systems : a comparison of existing approaches (2006)
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- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Beppler, F.D.; Fonseca, F.T.; Pacheco, R.C.S.: Hermeneus: an architecture for an ontology-enabled information retrieval (2008)
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- Date
- 28.11.2016 12:43:22
- Source
- http://www.personal.psu.edu/faculty/f/u/fuf1/hermeneus/Hermeneus_architecture.pdf
-
Reiner, U.: Automatische DDC-Klassifizierung bibliografischer Titeldatensätze der Deutschen Nationalbibliografie (2009)
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- Abstract
- Das Klassifizieren von Objekten (z. B. Fauna, Flora, Texte) ist ein Verfahren, das auf menschlicher Intelligenz basiert. In der Informatik - insbesondere im Gebiet der Künstlichen Intelligenz (KI) - wird u. a. untersucht, inweit Verfahren, die menschliche Intelligenz benötigen, automatisiert werden können. Hierbei hat sich herausgestellt, dass die Lösung von Alltagsproblemen eine größere Herausforderung darstellt, als die Lösung von Spezialproblemen, wie z. B. das Erstellen eines Schachcomputers. So ist "Rybka" der seit Juni 2007 amtierende Computerschach-Weltmeistern. Inwieweit Alltagsprobleme mit Methoden der Künstlichen Intelligenz gelöst werden können, ist eine - für den allgemeinen Fall - noch offene Frage. Beim Lösen von Alltagsproblemen spielt die Verarbeitung der natürlichen Sprache, wie z. B. das Verstehen, eine wesentliche Rolle. Den "gesunden Menschenverstand" als Maschine (in der Cyc-Wissensbasis in Form von Fakten und Regeln) zu realisieren, ist Lenat's Ziel seit 1984. Bezüglich des KI-Paradeprojektes "Cyc" gibt es CycOptimisten und Cyc-Pessimisten. Das Verstehen der natürlichen Sprache (z. B. Werktitel, Zusammenfassung, Vorwort, Inhalt) ist auch beim intellektuellen Klassifizieren von bibliografischen Titeldatensätzen oder Netzpublikationen notwendig, um diese Textobjekte korrekt klassifizieren zu können. Seit dem Jahr 2007 werden von der Deutschen Nationalbibliothek nahezu alle Veröffentlichungen mit der Dewey Dezimalklassifikation (DDC) intellektuell klassifiziert.
Die Menge der zu klassifizierenden Veröffentlichungen steigt spätestens seit der Existenz des World Wide Web schneller an, als sie intellektuell sachlich erschlossen werden kann. Daher werden Verfahren gesucht, um die Klassifizierung von Textobjekten zu automatisieren oder die intellektuelle Klassifizierung zumindest zu unterstützen. Seit 1968 gibt es Verfahren zur automatischen Dokumentenklassifizierung (Information Retrieval, kurz: IR) und seit 1992 zur automatischen Textklassifizierung (ATC: Automated Text Categorization). Seit immer mehr digitale Objekte im World Wide Web zur Verfügung stehen, haben Arbeiten zur automatischen Textklassifizierung seit ca. 1998 verstärkt zugenommen. Dazu gehören seit 1996 auch Arbeiten zur automatischen DDC-Klassifizierung bzw. RVK-Klassifizierung von bibliografischen Titeldatensätzen und Volltextdokumenten. Bei den Entwicklungen handelt es sich unseres Wissens bislang um experimentelle und keine im ständigen Betrieb befindlichen Systeme. Auch das VZG-Projekt Colibri/DDC ist seit 2006 u. a. mit der automatischen DDC-Klassifizierung befasst. Die diesbezüglichen Untersuchungen und Entwicklungen dienen zur Beantwortung der Forschungsfrage: "Ist es möglich, eine inhaltlich stimmige DDC-Titelklassifikation aller GVK-PLUS-Titeldatensätze automatisch zu erzielen?"
- Date
- 22. 1.2010 14:41:24
-
Greenberg, J.; Pattuelli, M.; Parsia, B.; Robertson, W.: Author-generated Dublin Core Metadata for Web Resources : A Baseline Study in an Organization (2002)
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-
Höfig, W.: Digitale Enzyklopädien : CD-ROM-Ausgaben: Meyers großes Konversations-Lexikon; Brockhaus, Die Enzyklopädie digital; Encyclopædia Britannica 2002 (2004)
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-
Bradford, R.B.: Relationship discovery in large text collections using Latent Semantic Indexing (2006)
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- Source
- Proceedings of the Fourth Workshop on Link Analysis, Counterterrorism, and Security, SIAM Data Mining Conference, Bethesda, MD, 20-22 April, 2006. [http://www.siam.org/meetings/sdm06/workproceed/Link%20Analysis/15.pdf]
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Nielsen, R.D.; Ward, W.; Martin, J.H.; Palmer, M.: Extracting a representation from text for semantic analysis (2008)
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-
Bartol, W.; Pióro, K.; Rosselló, F.: On the coverings by tolerance classes (2003)
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-
Harzing, A.-W.: Comparing the Google Scholar h-index with the ISI Journal Impact Factor (2008)
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-
Maaten, L. van den: Learning a parametric embedding by preserving local structure (2009)
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- Source
- Proceedings of the Twelfth International Conference on Artificial Intelligence & Statistics (AI-STATS), JMLR W&CP 5, 2009. S.384-391
-
Umstätter, W.: DDC in Europa : Hat der Einsatz in der Deutschen Nationalbibliothek unsere Zunft weitergebracht? Hat unsere Klientel etwas davon? (2008)
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-
Van der Veer Martens, B.: Do citation systems represent theories of truth? (2001)
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- Date
- 22. 7.2006 15:22:28
-
Bartolo, L.M.; Lowe, C.S.; Sadoway, D.R.; Powell, A.C.; Glotzer, S.C.: NSDL MatDL : exploring digital library roles (2005)
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- Abstract
- A primary goal of the NSDL Materials Digital Library (MatDL) is to bring materials science research and education closer together. MatDL is exploring the various roles digital libraries can serve in the materials science community including: 1) supporting a virtual lab, 2) developing markup language applications, and 3) building tools for metadata capture. MatDL is being integrated into an MIT virtual laboratory experience. Early student self-assessment survey results expressed positive opinions of the potential value of MatDL in supporting a virtual lab and in accomplishing additional educational objectives. A separate survey suggested that the effectiveness of a virtual lab may approach that of a physical lab on some laboratory learning objectives. MatDL is collaboratively developing a materials property grapher (KSU and MIT) and a submission tool (KSU and U-M). MatML is an extensible markup language for exchanging materials information developed by materials data experts in industry, government, standards organizations, and professional societies. The web-based MatML grapher allows students to compare selected materials properties across approximately 80 MatML-tagged materials. The MatML grapher adds value in this educational context by allowing students to utilize real property data to make optimal material selection decisions. The submission tool has been integrated into the regular workflow of U-M students and researchers generating nanostructure images. It prompts users for domain-specific information, automatically generating and attaching keywords and editable descriptions.
-
Qin, J.; Paling, S.: Converting a controlled vocabulary into an ontology : the case of GEM (2001)
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- Date
- 24. 8.2005 19:20:22
-
Schallier, W.: Why organize information if you can find it? : UDC and libraries in an Internet world (2007)
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-
Hitchcock, S.; Bergmark, D.; Brody, T.; Gutteridge, C.; Carr, L.; Hall, W.; Lagoze, C.; Harnad, S.: Open citation linking : the way forward (2002)
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Wang, Y.-H.; Jhuo, P.-S.: ¬A semantic faceted search with rule-based inference (2009)
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- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Prieto-Díaz, R.: ¬A faceted approach to building ontologies (2002)
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- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Birmingham, W.; Pardo, B.; Meek, C.; Shifrin, J.: ¬The MusArt music-retrieval system (2002)
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-
Duval, E.; Hodgins, W.; Sutton, S.; Weibel, S.L.: Metadata principles and practicalities (2002)
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