Search (75 results, page 1 of 4)

  • × theme_ss:"Automatisches Indexieren"
  1. Stankovic, R. et al.: Indexing of textual databases based on lexical resources : a case study for Serbian (2016) 0.03 
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    Date
    1. 2.2016 18:25:22
    Source
    Semantic keyword-based search on structured data sources: First COST Action IC1302 International KEYSTONE Conference, IKC 2015, Coimbra, Portugal, September 8-9, 2015. Revised Selected Papers. Eds.: J. Cardoso et al
  2. Milstead, J.L.: Thesauri in a full-text world (1998) 0.02 
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    Date
    22. 9.1997 19:16:05
    Source
    Visualizing subject access for 21st century information resources: Papers presented at the 1997 Clinic on Library Applications of Data Processing, 2-4 Mar 1997, Graduate School of Library and Information Science, University of Illinois at Urbana-Champaign. Ed.: P.A. Cochrane et al
  3. Junger, U.; Schwens, U.: ¬Die inhaltliche Erschließung des schriftlichen kulturellen Erbes auf dem Weg in die Zukunft : Automatische Vergabe von Schlagwörtern in der Deutschen Nationalbibliothek (2017) 0.02 
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    Abstract
    Wir leben im 21. Jahrhundert, und vieles, was vor hundert und noch vor fünfzig Jahren als Science Fiction abgetan worden wäre, ist mittlerweile Realität. Raumsonden fliegen zum Mars, machen dort Experimente und liefern Daten zur Erde zurück. Roboter werden für Routineaufgaben eingesetzt, zum Beispiel in der Industrie oder in der Medizin. Digitalisierung, künstliche Intelligenz und automatisierte Verfahren sind kaum mehr aus unserem Alltag wegzudenken. Grundlage vieler Prozesse sind lernende Algorithmen. Die fortschreitende digitale Transformation ist global und umfasst alle Lebens- und Arbeitsbereiche: Wirtschaft, Gesellschaft und Politik. Sie eröffnet neue Möglichkeiten, von denen auch Bibliotheken profitieren. Der starke Anstieg digitaler Publikationen, die einen wichtigen und prozentual immer größer werdenden Teil des Kulturerbes darstellen, sollte für Bibliotheken Anlass sein, diese Möglichkeiten aktiv aufzugreifen und einzusetzen. Die Auswertbarkeit digitaler Inhalte, beispielsweise durch Text- and Data-Mining (TDM), und die Entwicklung technischer Verfahren, mittels derer Inhalte miteinander vernetzt und semantisch in Beziehung gesetzt werden können, bieten Raum, auch bibliothekarische Erschließungsverfahren neu zu denken. Daher beschäftigt sich die Deutsche Nationalbibliothek (DNB) seit einigen Jahren mit der Frage, wie sich die Prozesse bei der Erschließung von Medienwerken verbessern und maschinell unterstützen lassen. Sie steht dabei im regelmäßigen kollegialen Austausch mit anderen Bibliotheken, die sich ebenfalls aktiv mit dieser Fragestellung befassen, sowie mit europäischen Nationalbibliotheken, die ihrerseits Interesse an dem Thema und den Erfahrungen der DNB haben. Als Nationalbibliothek mit umfangreichen Beständen an digitalen Publikationen hat die DNB auch Expertise bei der digitalen Langzeitarchivierung aufgebaut und ist im Netzwerk ihrer Partner als kompetente Gesprächspartnerin geschätzt.
    Date
    19. 8.2017 9:24:22
  4. Salton, G.; Allen, J.; Buckley, C.; Singhal, A.: Automatic analysis, theme generation, and summarization of machine-readable data (1994) 0.01 
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  5. Gross, D.: Maschinelle Bilderkennung mit Big Data und Deep Learning (2017) 0.01 
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    Abstract
    Die Arbeit mit unstrukturierten Daten dient gerne als Paradebeispiel für Big Data, weil die technologischen Möglichkeiten das Speichern und Verarbeiten großer Datenmengen erlauben und die Mehrheit dieser Daten unstrukturiert ist. Allerdings ist im Zusammenhang mit unstrukturierten Daten meist von der Analyse und der Extraktion von Informationen aus Texten die Rede. Viel weniger hingegen wird das Thema der Bildanalyse thematisiert. Diese gilt aber nach wie vor als eine Königdisziplin der modernen Computerwissenschaft.
    Source
    https://jaxenter.de/big-data-bildanalyse-50313
  6. Nohr, H.: Grundlagen der automatischen Indexierung : ein Lehrbuch (2003) 0.01 
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    Date
    22. 6.2009 12:46:51
    Footnote
    Im fünften Kapitel "Information Extraction" geht Nohr auf eine Problemstellung ein, die in der Fachwelt eine noch stärkere Betonung verdiente: "Die stetig ansteigende Zahl elektronischer Dokumente macht neben einer automatischen Erschließung auch eine automatische Gewinnung der relevanten Informationen aus diesen Dokumenten wünschenswert, um diese z.B. für weitere Bearbeitungen oder Auswertungen in betriebliche Informationssysteme übernehmen zu können." (S. 103) "Indexierung und Retrievalverfahren" als voneinander abhängige Verfahren werden im sechsten Kapitel behandelt. Hier stehen Relevance Ranking und Relevance Feedback sowie die Anwendung informationslinguistischer Verfahren in der Recherche im Mittelpunkt. Die "Evaluation automatischer Indexierung" setzt den thematischen Schlusspunkt. Hier geht es vor allem um die Oualität einer Indexierung, um gängige Retrievalmaße in Retrievaltest und deren Einssatz. Weiterhin ist hervorzuheben, dass jedes Kapitel durch die Vorgabe von Lernzielen eingeleitet wird und zu den jeweiligen Kapiteln (im hinteren Teil des Buches) einige Kontrollfragen gestellt werden. Die sehr zahlreichen Beispiele aus der Praxis, ein Abkürzungsverzeichnis und ein Sachregister erhöhen den Nutzwert des Buches. Die Lektüre förderte beim Rezensenten das Verständnis für die Zusammenhänge von BID-Handwerkzeug, Wirtschaftsinformatik (insbesondere Data Warehousing) und Künstlicher Intelligenz. Die "Grundlagen der automatischen Indexierung" sollte auch in den bibliothekarischen Studiengängen zur Pflichtlektüre gehören. Holger Nohrs Lehrbuch ist auch für den BID-Profi geeignet, um die mehr oder weniger fundierten Kenntnisse auf dem Gebiet "automatisches Indexieren" schnell, leicht verständlich und informativ aufzufrischen."
  7. Alexander, M.: Retrieving digital data with fuzzy matching (1997) 0.01 
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    Abstract
    In 1993 the British Library established a programme of activities entitled Initiatives for Access (IFA) to identify and develop computer applications based on the new technologies emerging in the aereas of digital and network service. Discusses the problem of the effective retrieval of digital data after its capture focusing on the product Excalibur EFS which looks at the way information is sorted at its fundamental level and identifies patterns in numbers. Looks at the benefits of Excalibur and outlines other experiments in progress as part of the IFA programme
  8. Fox, C.: Lexical analysis and stoplists (1992) 0.01 
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    Abstract
    Lexical analysis is a fundamental operation in both query processing and automatic indexing, and filtering stoplist words is an important step in the automatic indexing process. Presents basic algorithms and data structures for lexical analysis, and shows how stoplist word removal can be efficiently incorporated into lexical analysis
    Source
    Information retrieval: data structures and algorithms. Ed.: W.B. Frakes u. R. Baeza-Yates
  9. Milstead, J.L.: Methodologies for subject analysis in bibliographic databases (1992) 0.01 
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    Abstract
    The goal of the study was to determine the state of the art of subject analysis as applied to large bibliographic data bases. The intent was to gather and evaluate information, casting it in a form that could be applied by management. There was no attempt to determine actual costs or trade-offs among costs and possible benefits. Commercial automatic indexing packages were also reviewed. The overall conclusion was that data base producers should begin working seriously on upgrading their thesauri and codifying their indexing policies as a means of moving toward development of machine aids to indexing, but that fully automatic indexing is not yet ready for wholesale implementation
  10. Gödert, W.; Liebig, M.: Maschinelle Indexierung auf dem Prüfstand : Ergebnisse eines Retrievaltests zum MILOS II Projekt (1997) 0.01 
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    Abstract
    The test ran between Nov 95-Aug 96 in Cologne Fachhochschule fur Bibliothekswesen (College of Librarianship).The test basis was a database of 190,000 book titles published between 1990-95. MILOS II mechanized indexing methods proved helpful in avoiding or reducing numbers of unsatisfied/no result retrieval searches. Retrieval from mechanised indexing is 3 times more successful than from title keyword data. MILOS II also used a standardized semantic vocabulary. Mechanised indexing demands high quality software and output data
  11. Gábor, K.; Zargayouna, H.; Tellier, I.; Buscaldi, D.; Charnois, T.: ¬A typology of semantic relations dedicated to scientific literature analysis (2016) 0.01 
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    Abstract
    We propose a method for improving access to scientific literature by analyzing the content of research papers beyond citation links and topic tracking. Our model relies on a typology of explicit semantic relations. These relations are instantiated in the abstract/introduction part of the papers and can be identified automatically using textual data and external ontologies. Preliminary results show a promising precision in unsupervised relationship classification.
    Content
    Vortrag, "Semantics, Analytics, Visualisation: Enhancing Scholarly Data Workshop co-located with the 25th International World Wide Web Conference April 11, 2016 - Montreal, Canada", Montreal 2016.
  12. 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
  13. Strobel, S.; Marín-Arraiza, P.: Metadata for scientific audiovisual media : current practices and perspectives of the TIB / AV-portal (2015) 0.01 
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    Abstract
    Descriptive metadata play a key role in finding relevant search results in large amounts of unstructured data. However, current scientific audiovisual media are provided with little metadata, which makes them hard to find, let alone individual sequences. In this paper, the TIB / AV-Portal is presented as a use case where methods concerning the automatic generation of metadata, a semantic search and cross-lingual retrieval (German/English) have already been applied. These methods result in a better discoverability of the scientific audiovisual media hosted in the portal. Text, speech, and image content of the video are automatically indexed by specialised GND (Gemeinsame Normdatei) subject headings. A semantic search is established based on properties of the GND ontology. The cross-lingual retrieval uses English 'translations' that were derived by an ontology mapping (DBpedia i. a.). Further ways of increasing the discoverability and reuse of the metadata are publishing them as Linked Open Data and interlinking them with other data sets.
  14. Fuhr, N.; Niewelt, B.: ¬Ein Retrievaltest mit automatisch indexierten Dokumenten (1984) 0.01 
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    Date
    20.10.2000 12:22:23
  15. 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
  16. Advances in intelligent retrieval: Proc. of a conference ... Wadham College, Oxford, 16.-17.4.1985 (1986) 0.01 
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    Content
    Enthält die Beiträge: ADDIS, T.: Extended relational analysis: a design approach to knowledge-based systems; PARKINSON, D.: Supercomputers and non-numeric processing; McGREGOR, D.R. u. J.R. MALONE: An architectural approach to advances in information retrieval; ALLEN, M.J. u. O.S. HARRISON: Word processing and information retrieval: some practical problems; MURTAGH, F.: Clustering and nearest neighborhood searching; ENSER, P.G.B.: Experimenting with the automatic classification of books; TESKEY, N. u. Z. RAZAK: An analysis of ranking for free text retrieval systems; ZARRI, G.P.: Interactive information retrieval: an artificial intelligence approach to deal with biographical data; HANCOX, P. u. F. SMITH: A case system processor for the PRECIS indexing language; ROUAULT, J.: Linguistic methods in information retrieval systems; ARAGON-RAMIREZ, V. u. C.D. PAICE: Design of a system for the online elucidation of natural language search statements; BROOKS, H.M., P.J. DANIELS u. N.J. BELKIN: Problem descriptions and user models: developing an intelligent interface for document retrieval systems; BLACK, W.J., P. HARGREAVES u. P.B. MAYES: HEADS: a cataloguing advisory system; BELL, D.A.: An architecture for integrating data, knowledge, and information bases
  17. Polity, Y.: Vers une ergonomie linguistique (1994) 0.01 
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    Abstract
    Analyzed a special type of man-mchine interaction, that of searching an information system with natural language. A model for full text processing for information retrieval was proposed that considered the system's users and how they employ information. Describes how INIST (the National Institute for Scientific and Technical Information) is developing computer assisted indexing as an aid to improving relevance when retrieving information from bibliographic data banks
  18. Alexander, M.: Retrieving digital data with fuzzy matching (1996) 0.01 
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  19. Hirawa, M.: Role of keywords in the network searching era (1998) 0.01 
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    Abstract
    A survey of Japanese OPACs available on the Internet was conducted relating to use of keywords for subject access. The findings suggest that present OPACs are not capable of storing subject-oriented information. Currently available keyword access derives from a merely title-based retrieval system. Contents data should be added to bibliographic records as an efficient way of providing subject access, and costings for this process should be estimated. Word standardisation issues must also be addressed
  20. Fuhr, N.: Ranking-Experimente mit gewichteter Indexierung (1986) 0.01 
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    Date
    14. 6.2015 22:12:44

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