Search (53 results, page 1 of 3)

  • × theme_ss:"Automatisches Indexieren"
  1. Probst, M.; Mittelbach, J.: Maschinelle Indexierung in der Sacherschließung wissenschaftlicher Bibliotheken (2006) 0.09 
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    Content
    Vgl. unter: http://www.bibliothek-saur.de/2006_2/168-176.pdf.
    Date
    22. 3.2008 12:35:19
    Source
    Bibliothek: Forschung und Praxis. 30(2006) H.2, S.168-176
  2. Zimmermann, H.H.: Wortrelationierung in der Sprachtechnik : Stilhilfen, Retrievalhilfen, Übersetzungshilfen (1992) 0.04 
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    Kognitive Ansätze zum Ordnen und Darstellen von Wissen. 2. Tagung der Deutschen ISKO Sektion einschl. der Vorträge des Workshops "Thesauri als Werkzeuge der Sprachtechnologie", Weilburg, 15.-18.10.1991
  3. Fuhr, N.; Niewelt, B.: ¬Ein Retrievaltest mit automatisch indexierten Dokumenten (1984) 0.04 
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    Date
    20.10.2000 12:22:23
  4. Kutschekmanesch, S.; Lutes, B.; Moelle, K.; Thiel, U.; Tzeras, K.: Automated multilingual indexing : a synthesis of rule-based and thesaurus-based methods (1998) 0.03 
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    Source
    Information und Märkte: 50. Deutscher Dokumentartag 1998, Kongreß der Deutschen Gesellschaft für Dokumentation e.V. (DGD), Rheinische Friedrich-Wilhelms-Universität Bonn, 22.-24. September 1998. Hrsg. von Marlies Ockenfeld u. Gerhard J. Mantwill
  5. Martins, A.L.; Souza, R.R.; Ribeiro de Mello, H.: ¬The use of noun phrases in information retrieval : proposing a mechanism for automatic classification (2014) 0.01 
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    Abstract
    This paper presents a research on syntactic structures known as noun phrases (NP) being applied to increase the effectiveness and efficiency of the mechanisms for the document's classification. Our hypothesis is the fact that the NP can be used instead of single words as a semantic aggregator to reduce the number of words that will be used for the classification system without losing its semantic coverage, increasing its efficiency. The experiment divided the documents classification process in three phases: a) NP preprocessing b) system training; and c) classification experiments. In the first step, a corpus of digitalized texts was submitted to a natural language processing platform1 in which the part-of-speech tagging was done, and them PERL scripts pertaining to the PALAVRAS package were used to extract the Noun Phrases. The preprocessing also involved the tasks of a) removing NP low meaning pre-modifiers, as quantifiers; b) identification of synonyms and corresponding substitution for common hyperonyms; and c) stemming of the relevant words contained in the NP, for similitude checking with other NPs. The first tests with the resulting documents have demonstrated its effectiveness. We have compared the structural similarity of the documents before and after the whole pre-processing steps of phase one. The texts maintained the consistency with the original and have kept the readability. The second phase involves submitting the modified documents to a SVM algorithm to identify clusters and classify the documents. The classification rules are to be established using a machine learning approach. Finally, tests will be conducted to check the effectiveness of the whole process.
    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
  6. Gaus, W.; Kaluscha, R.: Maschinelle inhaltliche Erschließung von Arztbriefen und Auswertung von Reha-Entlassungsberichten (2006) 0.01 
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    Pages
    S.159-168
  7. Yusuff, A.: Automatisches Indexing and Abstracting : Grundlagen und Beispiele (2002) 0.01 
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    Imprint
    Potsdam : Fachhochschule, FB A-B-D
  8. Thirion, B.; Leroy, J.P.; Baudic, F.; Douyère, M.; Piot, J.; Darmoni, S.J.: SDI selecting, decribing, and indexing : did you mean automatically? (2001) 0.01 
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  9. Greiner-Petter, A.; Schubotz, M.; Cohl, H.S.; Gipp, B.: Semantic preserving bijective mappings for expressions involving special functions between computer algebra systems and document preparation systems (2019) 0.01 
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    Date
    20. 1.2015 18:30:22
  10. Wiesenmüller, H.: DNB-Sacherschließung : Neues für die Reihen A und B (2019) 0.01 
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    Abstract
    "Alle paar Jahre wird die Bibliothekscommunity mit Veränderungen in der inhaltlichen Erschließung durch die Deutsche Nationalbibliothek konfrontiert. Sicher werden sich viele noch an die Einschnitte des Jahres 2014 für die Reihe A erinnern: Seither werden u.a. Ratgeber, Sprachwörterbücher, Reiseführer und Kochbücher nicht mehr mit Schlagwörtern erschlossen (vgl. das DNB-Konzept von 2014). Das Jahr 2017 brachte die Einführung der maschinellen Indexierung für die Reihen B und H bei gleichzeitigem Verlust der DDC-Tiefenerschließung (vgl. DNB-Informationen von 2017). Virulent war seither die Frage, was mit der Reihe A passieren würde. Seit wenigen Tagen kann man dies nun auf der Website der DNB nachlesen. (Nebenbei: Es ist zu befürchten, dass viele Links in diesem Blog-Beitrag in absehbarer Zeit nicht mehr funktionieren werden, da ein Relaunch der DNB-Website angekündigt ist. Wie beim letzten Mal wird es vermutlich auch diesmal keine Weiterleitungen von den alten auf die neuen URLs geben.)"
    Source
    https://www.basiswissen-rda.de/dnb-sacherschliessung-reihen-a-und-b/
  11. Thönssen, B.: Automatische Indexierung und Schnittstellen zu Thesauri (1988) 0.01 
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  12. Biebricher, P.; Fuhr, N.; Niewelt, B.: ¬Der AIR-Retrievaltest (1986) 0.01 
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  13. Gil-Leiva, I.; Munoz, J.V.R.: Analisis de los descriptores de diferentes areas del conocimiento indizades en bases de datos del CSIC : Aplicacion a la indizacion automatica (1997) 0.01 
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    Field
    Psychologie
  14. 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
  15. Voorhees, E.M.: Implementing agglomerative hierarchic clustering algorithms for use in document retrieval (1986) 0.01 
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    Source
    Information processing and management. 22(1986) no.6, S.465-476
  16. Krutulis, J.D.; Jacob, E.K.: ¬A theoretical model for the study of emergent structure in adaptive information networks (1995) 0.01 
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    Source
    Connectedness: information, systems, people, organizations. Proceedings of CAIS/ACSI 95, the proceedings of the 23rd Annual Conference of the Canadian Association for Information Science. Ed. by Hope A. Olson and Denis B. Ward
  17. Siebenkäs, A.; Markscheffel, B.: Conception of a workflow for the semi-automatic construction of a thesaurus for the German printing industry (2015) 0.01 
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  18. Wiesenmüller, H.: Maschinelle Indexierung am Beispiel der DNB : Analyse und Entwicklungmöglichkeiten (2018) 0.01 
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    Abstract
    Der Beitrag untersucht die Ergebnisse des bei der Deutschen Nationalbibliothek (DNB) eingesetzten Verfahrens zur automatischen Vergabe von Schlagwörtern. Seit 2017 kommt dieses auch bei Printausgaben der Reihen B und H der Deutschen Nationalbibliografie zum Einsatz. Die zentralen Problembereiche werden dargestellt und an Beispielen illustriert - beispielsweise dass nicht alle im Inhaltsverzeichnis vorkommenden Wörter tatsächlich thematische Aspekte ausdrücken und dass die Software sehr häufig Körperschaften und andere "Named entities" nicht erkennt. Die maschinell generierten Ergebnisse sind derzeit sehr unbefriedigend. Es werden Überlegungen für mögliche Verbesserungen und sinnvolle Strategien angestellt.
  19. Hlava, M.M.K.: Automatic indexing : comparing rule-based and statistics-based indexing systems (2005) 0.01 
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    Source
    Information outlook. 9(2005) no.8, S.22-23
  20. 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.

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