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  • × year_i:[2000 TO 2010}
  • × theme_ss:"Automatisches Indexieren"
  1. Nohr, H.: Grundlagen der automatischen Indexierung : ein Lehrbuch (2003) 0.01 
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    Date
    22. 6.2009 12:46:51
    Footnote
    Rez. in: nfd 54(2003) H.5, S.314 (W. Ratzek): "Um entscheidungsrelevante Daten aus der ständig wachsenden Flut von mehr oder weniger relevanten Dokumenten zu extrahieren, müssen Unternehmen, öffentliche Verwaltung oder Einrichtungen der Fachinformation effektive und effiziente Filtersysteme entwickeln, einsetzen und pflegen. Das vorliegende Lehrbuch von Holger Nohr bietet erstmalig eine grundlegende Einführung in das Thema "automatische Indexierung". Denn: "Wie man Information sammelt, verwaltet und verwendet, wird darüber entscheiden, ob man zu den Gewinnern oder Verlierern gehört" (Bill Gates), heißt es einleitend. Im ersten Kapitel "Einleitung" stehen die Grundlagen im Mittelpunkt. Die Zusammenhänge zwischen Dokumenten-Management-Systeme, Information Retrieval und Indexierung für Planungs-, Entscheidungs- oder Innovationsprozesse, sowohl in Profit- als auch Non-Profit-Organisationen werden beschrieben. Am Ende des einleitenden Kapitels geht Nohr auf die Diskussion um die intellektuelle und automatische Indexierung ein und leitet damit über zum zweiten Kapitel "automatisches Indexieren. Hier geht der Autor überblickartig unter anderem ein auf - Probleme der automatischen Sprachverarbeitung und Indexierung - verschiedene Verfahren der automatischen Indexierung z.B. einfache Stichwortextraktion / Volltextinvertierung, - statistische Verfahren, Pattern-Matching-Verfahren. Die "Verfahren der automatischen Indexierung" behandelt Nohr dann vertiefend und mit vielen Beispielen versehen im umfangreichsten dritten Kapitel. Das vierte Kapitel "Keyphrase Extraction" nimmt eine Passpartout-Status ein: "Eine Zwischenstufe auf dem Weg von der automatischen Indexierung hin zur automatischen Generierung textueller Zusammenfassungen (Automatic Text Summarization) stellen Ansätze dar, die Schlüsselphrasen aus Dokumenten extrahieren (Keyphrase Extraction). Die Grenzen zwischen den automatischen Verfahren der Indexierung und denen des Text Summarization sind fließend." (S. 91). Am Beispiel NCR"s Extractor/Copernic Summarizer beschreibt Nohr die Funktionsweise.
  2. 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
  3. Hauer, M.: Automatische Indexierung (2000) 0.01 
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    Source
    Wissen in Aktion: Wege des Knowledge Managements. 22. Online-Tagung der DGI, Frankfurt am Main, 2.-4.5.2000. Proceedings. Hrsg.: R. Schmidt
  4. Anderson, J.D.; Pérez-Carballo, J.: ¬The nature of indexing: how humans and machines analyze messages and texts for retrieval : Part I: Research and the nature of human indexing (2001) 0.01 
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    Source
    Information processing and management. 37(2001) no.2, S.231-254
  5. 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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    Source
    Information processing and management. 37(2001) no.2, S.255-277
  6. Lepsky, K.; Vorhauer, J.: Lingo - ein open source System für die Automatische Indexierung deutschsprachiger Dokumente (2006) 0.01 
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    Date
    24. 3.2006 12:22:02
  7. Probst, M.; Mittelbach, J.: Maschinelle Indexierung in der Sacherschließung wissenschaftlicher Bibliotheken (2006) 0.01 
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    Date
    22. 3.2008 12:35:19
  8. Renz, M.: Automatische Inhaltserschließung im Zeichen von Wissensmanagement (2001) 0.01 
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    Date
    22. 3.2001 13:14:48
  9. Newman, D.J.; Block, S.: Probabilistic topic decomposition of an eighteenth-century American newspaper (2006) 0.01 
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    Date
    22. 7.2006 17:32:00
  10. Pulgarin, A.; Gil-Leiva, I.: Bibliometric analysis of the automatic indexing literature : 1956-2000 (2004) 0.01 
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    Source
    Information processing and management. 40(2004) no.2, S.365-377
  11. Lorenz, S.: Konzeption und prototypische Realisierung einer begriffsbasierten Texterschließung (2006) 0.00 
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    Date
    22. 3.2015 9:17:30
  12. Mansour, N.; Haraty, R.A.; Daher, W.; Houri, M.: ¬An auto-indexing method for Arabic text (2008) 0.00 
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    Information processing and management. 44(2008) no.4, S.1538-1545
  13. Snajder, J.; Dalbelo Basic, B.D.; Tadic, M.: Automatic acquisition of inflectional lexica for morphological normalisation (2008) 0.00 
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    Information processing and management. 44(2008) no.5, S.1720-1731
  14. Rapke, K.: Automatische Indexierung von Volltexten für die Gruner+Jahr Pressedatenbank (2001) 0.00 
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    Information Research & Content Management: Orientierung, Ordnung und Organisation im Wissensmarkt; 23. DGI-Online-Tagung der DGI und 53. Jahrestagung der Deutschen Gesellschaft für Informationswissenschaft und Informationspraxis e.V. DGI, Frankfurt am Main, 8.-10.5.2001. Proceedings. Hrsg.: R. Schmidt
  15. Li, W.; Wong, K.-F.; Yuan, C.: Toward automatic Chinese temporal information extraction (2001) 0.00 
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    Abstract
    Over the past few years, temporal information processing and temporal database management have increasingly become hot topics. Nevertheless, only a few researchers have investigated these areas in the Chinese language. This lays down the objective of our research: to exploit Chinese language processing techniques for temporal information extraction and concept reasoning. In this article, we first study the mechanism for expressing time in Chinese. On the basis of the study, we then design a general frame structure for maintaining the extracted temporal concepts and propose a system for extracting time-dependent information from Hong Kong financial news. In the system, temporal knowledge is represented by different types of temporal concepts (TTC) and different temporal relations, including absolute and relative relations, which are used to correlate between action times and reference times. In analyzing a sentence, the algorithm first determines the situation related to the verb. This in turn will identify the type of temporal concept associated with the verb. After that, the relevant temporal information is extracted and the temporal relations are derived. These relations link relevant concept frames together in chronological order, which in turn provide the knowledge to fulfill users' queries, e.g., for question-answering (i.e., Q&A) applications
  16. Ahlgren, P.; Kekäläinen, J.: Indexing strategies for Swedish full text retrieval under different user scenarios (2007) 0.00 
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    Information processing and management. 43(2007) no.1, S.81-102
  17. Tsai, C.-F.; McGarry, K.; Tait, J.: Qualitative evaluation of automatic assignment of keywords to images (2006) 0.00 
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    Information processing and management. 42(2006) no.1, S.136-154
  18. Nohr, H.: Theorie des Information Retrieval II : Automatische Indexierung (2004) 0.00 
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    Abstract
    Ein großer Teil der Informationen - Schätzungen zufolge bis zu 80% - liegt in Organisationen in unstrukturierten Dokumenten vor. In der Vergangenheit wurden Lösungen für das Management strukturierter Informationen entwickelt, die es nun auch zu erreichen gilt für unstrukturierte Informationen. Neben Verfahren des Data Mining für die Datenanalyse treten Versuche, Text Mining (Lit. 06) auf die Textanalyse anzuwenden. Um gezielt Dokumente im Repository suchen zu können, ist eine effektive Inhaltserkennung und -kennzeichnung erforderlich, d.h. eine Zuordnung der Dokumente zu Themengebieten bzw die Speicherung geeigneter Indexterme als Metadaten. Zu diesem Zweck müssen die Dokumenteninhalte repräsentiert, d.h. indexiert oder klassifiziert, werden. Dokumentanalyse dient auch der Steuerung des Informations- und Dokumentenflusses. Ziel ist die Einleitung eines "Workflow nach Posteingang". Eine Dokumentanalyse kann anhand erkannter Merkmale Eingangspost automatisch an den Sachbearbeiter oder die zuständige Organisationseinheit (Rechnungen in die Buchhaltung, Aufträge in den Vertrieb) im Unternehmen leiten. Dokumentanalysen werden auch benötigt, wenn Mitarbeiter über einen persönlichen Informationsfilter relevante Dokumente automatisch zugestellt bekommen sollen. Aufgrund der Systemintegration werden Indexierungslösungen in den Funktionsumfang von DMS- bzw. Workflow-Produkten integriert. Eine Architektur solcher Systeme zeigt Abb. 1. Die Architektur zeigt die Indexierungs- bzw. Klassifizierungsfunktion im Zentrum der Anwendung. Dabei erfüllt sie Aufgaben für die Repräsentation von Dokumenten (Metadaten) und das spätere Retrieval.
  19. Witschel, H.F.: Terminology extraction and automatic indexing : comparison and qualitative evaluation of methods (2005) 0.00 
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    Abstract
    Many terminology engineering processes involve the task of automatic terminology extraction: before the terminology of a given domain can be modelled, organised or standardised, important concepts (or terms) of this domain have to be identified and fed into terminological databases. These serve in further steps as a starting point for compiling dictionaries, thesauri or maybe even terminological ontologies for the domain. For the extraction of the initial concepts, extraction methods are needed that operate on specialised language texts. On the other hand, many machine learning or information retrieval applications require automatic indexing techniques. In Machine Learning applications concerned with the automatic clustering or classification of texts, often feature vectors are needed that describe the contents of a given text briefly but meaningfully. These feature vectors typically consist of a fairly small set of index terms together with weights indicating their importance. Short but meaningful descriptions of document contents as provided by good index terms are also useful to humans: some knowledge management applications (e.g. topic maps) use them as a set of basic concepts (topics). The author believes that the tasks of terminology extraction and automatic indexing have much in common and can thus benefit from the same set of basic algorithms. It is the goal of this paper to outline some methods that may be used in both contexts, but also to find the discriminating factors between the two tasks that call for the variation of parameters or application of different techniques. The discussion of these methods will be based on statistical, syntactical and especially morphological properties of (index) terms. The paper is concluded by the presentation of some qualitative and quantitative results comparing statistical and morphological methods.

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