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  • × theme_ss:"Automatisches Indexieren"
  1. Gaese, V.: "Automatische Klassifikation von Presseartikeln in der Gruner + Jahr Dokumentation" (2003) 0.02
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    Abstract
    Das Klassifizieren von Texten, auch Indexieren, inhaltliches Erschließen oder verschlagworten genannt, gehört seit jeher zu den zwar notwendigen aber sehr aufwändigen Aufgaben von Archiven bzw. Dokumentationen. Ihre unterschiedlichen Zwecke bzw. Anforderungen sind sicher ein Grund dafür, dass es fast ebenso viele Erschließungsinventare, Thesauri oder Schlagwortverzeichnisse wie Dokumentationen gibt. Im folgenden werden Klassifizierung, Indexierung, Erschließung und Verschlagwortung synonym verwendet. In der G+J Dokumentation arbeiten heute ca. 20 Dokumentare an Auswahl und Erschließung von täglich etwa 1.100 Artikeln aus insgesamt ca. 210 Titeln. In der G+J Pressedatenbank sind aktuell ca. 7 Mio Artikel gespeichert, gut 2 Mio als digitaler Volltext (OCR/Satzdaten). Archiviert sind nur Artikel, für die die G+J Dokumentation die entsprechenden Rechte hat.
  2. Pritchard, J.: Information retrieval : smarter indexing (1991) 0.01
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  3. Salton, G.; McGill, M. J.: Information Retrieval: Grundlegendes für Informationswissenschaftler (1987) 0.01
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  4. Salton, G.; Allan, J.; Buckley, C.; Singhal, A.: Automatic analysis, theme generation, and summarization of machine readable texts (1994) 0.01
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  5. Rapke, K.: Automatische Indexierung von Volltexten für die Gruner+Jahr Pressedatenbank (2001) 0.01
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    Abstract
    Retrievaltests sind die anerkannteste Methode, um neue Verfahren der Inhaltserschließung gegenüber traditionellen Verfahren zu rechtfertigen. Im Rahmen einer Diplomarbeit wurden zwei grundsätzlich unterschiedliche Systeme der automatischen inhaltlichen Erschließung anhand der Pressedatenbank des Verlagshauses Gruner + Jahr (G+J) getestet und evaluiert. Untersucht wurde dabei natürlichsprachliches Retrieval im Vergleich zu Booleschem Retrieval. Bei den beiden Systemen handelt es sich zum einen um Autonomy von Autonomy Inc. und DocCat, das von IBM an die Datenbankstruktur der G+J Pressedatenbank angepasst wurde. Ersteres ist ein auf natürlichsprachlichem Retrieval basierendes, probabilistisches System. DocCat demgegenüber basiert auf Booleschem Retrieval und ist ein lernendes System, das aufgrund einer intellektuell erstellten Trainingsvorlage indexiert. Methodisch geht die Evaluation vom realen Anwendungskontext der Textdokumentation von G+J aus. Die Tests werden sowohl unter statistischen wie auch qualitativen Gesichtspunkten bewertet. Ein Ergebnis der Tests ist, dass DocCat einige Mängel gegenüber der intellektuellen Inhaltserschließung aufweist, die noch behoben werden müssen, während das natürlichsprachliche Retrieval von Autonomy in diesem Rahmen und für die speziellen Anforderungen der G+J Textdokumentation so nicht einsetzbar ist
  6. Anderson, J.D.; Pérez-Carballo, J.: ¬The nature of indexing: how humans and machines analyze messages and texts for retrieval : Part II: Machine indexing, and the allocation of human versus machine effort (2001) 0.01
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  7. Peters, G.: Verschlagwortung und automatische Verfahren in der G+J Dokumentation (2003) 0.01
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  8. Experimentelles und praktisches Information Retrieval : Festschrift für Gerhard Lustig (1992) 0.01
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    Content
    Enthält die Beiträge: SALTON, G.: Effective text understanding in information retrieval; KRAUSE, J.: Intelligentes Information retrieval; FUHR, N.: Konzepte zur Gestaltung zukünftiger Information-Retrieval-Systeme; HÜTHER, H.: Überlegungen zu einem mathematischen Modell für die Type-Token-, die Grundform-Token und die Grundform-Type-Relation; KNORZ, G.: Automatische Generierung inferentieller Links in und zwischen Hyperdokumenten; KONRAD, E.: Zur Effektivitätsbewertung von Information-Retrieval-Systemen; HENRICHS, N.: Retrievalunterstützung durch automatisch generierte Wortfelder; LÜCK, W., W. RITTBERGER u. M. SCHWANTNER: Der Einsatz des Automatischen Indexierungs- und Retrieval-System (AIR) im Fachinformationszentrum Karlsruhe; REIMER, U.: Verfahren der Automatischen Indexierung. Benötigtes Vorwissen und Ansätze zu seiner automatischen Akquisition: Ein Überblick; ENDRES-NIGGEMEYER, B.: Dokumentrepräsentation: Ein individuelles prozedurales Modell des Abstracting, des Indexierens und Klassifizierens; SEELBACH, D.: Zur Entwicklung von zwei- und mehrsprachigen lexikalischen Datenbanken und Terminologiedatenbanken; ZIMMERMANN, H.: Der Einfluß der Sprachbarrieren in Europa und Möglichkeiten zu ihrer Minderung; LENDERS, W.: Wörter zwischen Welt und Wissen; PANYR, J.: Frames, Thesauri und automatische Klassifikation (Clusteranalyse): HAHN, U.: Forschungsstrategien und Erkenntnisinteressen in der anwendungsorientierten automatischen Sprachverarbeitung. Überlegungen zu einer ingenieurorientierten Computerlinguistik; KUHLEN, R.: Hypertext und Information Retrieval - mehr als Browsing und Suche.
  9. Mao, J.; Xu, W.; Yang, Y.; Wang, J.; Yuille, A.L.: Explain images with multimodal recurrent neural networks (2014) 0.01
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  10. Panyr, J.: Vektorraum-Modell und Clusteranalyse in Information-Retrieval-Systemen (1987) 0.01
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  11. Frants, V.I.; Kamenoff, N.I.; Shapiro, J.: ¬One approach to classification of users and automatic clustering of documents (1993) 0.01
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  12. Salton, G.; Buckley, C.; Allan, J.: Automatic structuring of text files (1992) 0.01
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  13. Salton, G.; Allan, J.; Singhal, A.: Automatic text decomposition and structuring (1996) 0.01
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  14. Panyr, J.: Automatische Indexierung und Klassifikation (1983) 0.01
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  15. Krause, J.; Womser-Hacker, C.: PADOK-II : Retrievaltests zur Bewertung von Volltextindexierungsvarianten für das deutsche Patentinformationssystem (1990) 0.01
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  16. Bredack, J.; Lepsky, K.: Automatische Extraktion von Fachterminologie aus Volltexten (2014) 0.01
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  17. Clavel, G.; Walther, F.; Walther, J.: Indexation automatique de fonds bibliotheconomiques (1993) 0.01
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  18. SIGIR'92 : Proceedings of the 15th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (1992) 0.01
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    Content
    HARMAN, D.: Relevance feedback revisited; AALBERSBERG, I.J.: Incremental relevance feedback; TAGUE-SUTCLIFFE, J.: Measuring the informativeness of a retrieval process; LEWIS, D.D.: An evaluation of phrasal and clustered representations on a text categorization task; BLOSSEVILLE, M.J., G. HÉBRAIL, M.G. MONTEIL u. N. PÉNOT: Automatic document classification: natural language processing, statistical analysis, and expert system techniques used together; MASAND, B., G. LINOFF u. D. WALTZ: Classifying news stories using memory based reasoning; KEEN, E.M.: Term position ranking: some new test results; CROUCH, C.J. u. B. YANG: Experiments in automatic statistical thesaurus construction; GREFENSTETTE, G.: Use of syntactic context to produce term association lists for text retrieval; ANICK, P.G. u. R.A. FLYNN: Versioning of full-text information retrieval system; BURKOWSKI, F.J.: Retrieval activities in a database consisting of heterogeneous collections; DEERWESTER, S.C., K. WACLENA u. M. LaMAR: A textual object management system; NIE, J.-Y.:Towards a probabilistic modal logic for semantic-based information retrieval; WANG, A.W., S.K.M. WONG u. Y.Y. YAO: An analysis of vector space models based on computational geometry; BARTELL, B.T., G.W. COTTRELL u. R.K. BELEW: Latent semantic indexing is an optimal special case of multidimensional scaling; GLAVITSCH, U. u. P. SCHÄUBLE: A system for retrieving speech documents; MARGULIS, E.L.: N-Poisson document modelling; HESS, M.: An incrementally extensible document retrieval system based on linguistics and logical principles; COOPER, W.S., F.C. GEY u. D.P. DABNEY: Probabilistic retrieval based on staged logistic regression; FUHR, N.: Integration of probabilistic fact and text retrieval; CROFT, B., L.A. SMITH u. H. TURTLE: A loosely-coupled integration of a text retrieval system and an object-oriented database system; DUMAIS, S.T. u. J. NIELSEN: Automating the assignement of submitted manuscripts to reviewers; GOST, M.A. u. M. MASOTTI: Design of an OPAC database to permit different subject searching accesses; ROBERTSON, A.M. u. P. WILLETT: Searching for historical word forms in a database of 17th century English text using spelling correction methods; FAX, E.A., Q.F. CHEN u. L.S. HEATH: A faster algorithm for constructing minimal perfect hash functions; MOFFAT, A. u. J. ZOBEL: Parameterised compression for sparse bitmaps; GRANDI, F., P. TIBERIO u. P. Zezula: Frame-sliced patitioned parallel signature files; ALLEN, B.: Cognitive differences in end user searching of a CD-ROM index; SONNENWALD, D.H.: Developing a theory to guide the process of designing information retrieval systems; CUTTING, D.R., J.O. PEDERSEN, D. KARGER, u. J.W. TUKEY: Scatter/ Gather: a cluster-based approach to browsing large document collections; CHALMERS, M. u. P. CHITSON: Bead: Explorations in information visualization; WILLIAMSON, C. u. B. SHNEIDERMAN: The dynamic HomeFinder: evaluating dynamic queries in a real-estate information exploring system
  19. Lepsky, K.; Siepmann, J.; Zimmermann, A.: Automatische Indexierung für Online-Kataloge : Ergebnisse eines Retrievaltests (1996) 0.01
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  20. Dolamic, L.; Savoy, J.: When stopword lists make the difference (2009) 0.01
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Years

Languages

  • e 56
  • d 38
  • f 2
  • a 1
  • m 1
  • ru 1
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Types

  • a 81
  • el 7
  • x 6
  • s 5
  • m 3
  • p 2
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