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  • × theme_ss:"Automatisches Abstracting"
  1. Haag, M.: Automatic text summarization : Evaluation des Copernic Summarizer und mögliche Einsatzfelder in der Fachinformation der DaimlerCrysler AG (2002) 0.06 
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    Abstract
    An evaluation of the Copernic Summarizer, a software for automatically summarizing text in various data formats, is being presented. It shall be assessed if and how the Copernic Summarizer can reasonably be used in the DaimlerChrysler Information Division in order to enhance the quality of its information services. First, an introduction into Automatic Text Summarization is given and the Copernic Summarizer is being presented. Various methods for evaluating Automatic Text Summarization systems and software ergonomics are presented. Two evaluation forms are developed with which the employees of the Information Division shall evaluate the quality and relevance of the extracted keywords and summaries as well as the software's usability. The quality and relevance assessment is done by comparing the original text to the summaries. Finally, a recommendation is given concerning the use of the Copernic Summarizer.
    Date
    27. 2.1999 16:23:24
    Footnote
    Diplomarbeit an der HBI Stuttgart. - Vgl. auch: nfd 53(2002) H.4, S.243-244
  2. Meyer, R.: Allein, es wär' so schön gewesen : Der Copernic Summarzier kann Internettexte leider nicht befriedigend und sinnvoll zusammenfassen (2002) 0.02 
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    Abstract
    Das Netz hat die Jagd nach textlichen Inhalten erheblich erleichtert. Es ist so ein-fach, irgendeinen Beitrag über ein bestimmtes Thema zu finden, daß man eher über Fülle als über Mangel klagt. Suchmaschinen und Kataloge helfen beim Sichten, indem sie eine Vorauswahl von Links treffen. Das Programm "Copernic Summarizer" geht einen anderen Weg: Es erstellt Exzerpte beliebiger Texte und will damit die Lesezeit verkürzen. Decken wir über die lästige Zwangsregistrierung (unter Pflichtangabe einer Mailadresse) das Mäntelchen des Schweigens. Was folgt, geht rasch, nicht nur die ersten Schritte sind schnell vollzogen. Die Software läßt sich in verschiedenen Umgebungen einsetzen. Unterstützt werden Microsoft Office, einige Mailprogramme sowie der Acrobat Reader für PDF-Dateien. Besonders eignet sich das Verfahren freilich für Internetseiten. Der "Summarizer" nistet sich im Browser als Symbol ein. Und mit einem Klick faßt er einen Online Text in einem Extrafenster zusammen. Es handelt sich dabei nicht im eigentlichen Sinne um eine Zusammenfassung mit eigenen Worten, die in Kürze den Gesamtgehalt wiedergibt. Das Ergebnis ist schlichtes Kürzen, das sich noch dazu ziemlich brutal vollzieht, da grundsätzlich vollständige Sätze gestrichen werden. Die Software erfaßt den Text, versucht Schlüsselwörter zu ermitteln und entscheidet danach, welche Sätze wichtig sind und welche nicht. Das Verfahren mag den Entwicklungsaufwand verringert haben, dem Anwender hingegen bereitet es Probleme. Oftmals beziehen sich Sätze auf frühere Aussagen, etwa in Formulierungen wie "Diese Methode wird . . ." oder "Ein Jahr später . . ." In der Zusammenfassung fehlt entweder der Kontext dazu oder man kann nicht darauf vertrauen, daß der Bezug sich tatsächlich im voranstehenden Satz findet. Die Liste der Schlüsselwörter, die links eingeblendet wird, wirkt nicht immer glücklich. Teilweise finden sich unauffällige Begriffe wie "Anlaß" oder "zudem". Wenigstens lassen sich einzelne Begriffe entfernen, um das Ergebnis zu verfeinern. Hilfreich ist das mögliche Markieren der Schlüsselbegriffe im Text. Unverständlich bleibt hingegen, weshalb man nicht selbst relevante Wörter festlegen darf, die als Basis für die Zusammenfassung dienen. Das Kürzen des Textes ist in mehreren Stufen möglich, von fünf bis fünfzig Prozent. Fünf Prozent sind unbrauchbar; ein guter Kompromiß sind fünfundzwanzig. Allerdings nimmt es die Software nicht genau mit den eigenen Vorgaben. Bei kürzeren Texten ist die Zusammenfassung von angeblich einem Viertel fast genauso lang wie das Original; noch bei zwei Seiten eng bedrucktem Text (8 Kilobyte) entspricht das Exzerpt einem Drittel des Originals. Für gewöhnlich sind Webseiten geschmückt mit einem Menü, mit Werbung, mit Hinweiskästen und allerlei mehr. Sehr zuverlässig erkennt die Software, was überhaupt Fließtext ist; alles andere wird ausgefiltert. Da bedauert man es zuweilen, daß der Summarizer nicht den kompletten Text listet, damit er in einer angenehmen Umgebung schwarz auf weiß gelesen oder gedruckt wird. Wahlweise zum manuellen Auslösen der Zusammenfassung wird der "LiveSummarizer" aktiviert. Er verdichtet Text zeitgleich mit dem Aufrufen einer Seite, nimmt dafür aber ein Drittel der Bildschirmfläche ein - ein zu hoher Preis. Insgesamt fragen wir uns, wie man das Programm sinnvoll nutzen soll. Beim Verdichten von Nachrichten ist unsicher, ob Summarizer nicht wichtige Details unterschlägt. Bei langen Texten sorgen Fragen zum Kontext für Verwirrung. Sucht man nach der Antwort auf eine Detailfrage, hilft die Suchfunktion des Browsers oft schneller. Eine Zusammenfassung hätte auch dem Preis gutgetan: 100 Euro verlangt der deutsche Verleger Softline. Das scheint deutlich zu hoch gegriffen. Zumal das Zusammenfassen der einzige Zweck des Summarizers ist. Das Verwalten von Bookmarks und das Archivieren von Texten wären sinnvolle Ergänzungen gewesen.
  3. Kuhlen, R.: In Richtung Summarizing für Diskurse in K3 (2006) 0.02 
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    Abstract
    Der Bedarf nach Summarizing-Leistungen, in Situationen der Fachinformation, aber auch in kommunikativen Umgebungen (Diskursen) wird aufgezeigt. Summarizing wird dazu in den Kontext des bisherigen (auch automatischen) Abstracting/Extracting gestellt. Der aktuelle Forschungsstand, vor allem mit Blick auf Multi-Document-Summarizing, wird dargestellt. Summarizing ist eine wichtige Funktion in komplex und umfänglich werdenden Diskussionen in elektronischen Foren. Dies wird am Beispiel des e-Learning-Systems K3 aufgezeigt. Rudimentäre Summarizing-Funktionen von K3 und des zugeordneten K3VIS-Systems werden dargestellt. Der Rahmen für ein elaborierteres, Template-orientiertes Summarizing unter Verwendung der vielfältigen Auszeichnungsfunktionen von K3 (Rollen, Diskurstypen, Inhaltstypen etc.) wird aufgespannt.
    Date
    13.10.2006 9:35:23
    Source
    Information und Sprache: Beiträge zu Informationswissenschaft, Computerlinguistik, Bibliothekswesen und verwandten Fächern. Festschrift für Harald H. Zimmermann. Herausgegeben von Ilse Harms, Heinz-Dirk Luckhardt und Hans W. Giessen
  4. Summarising software for publishing (1996) 0.02 
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    Abstract
    Reviews 4 software packages designed to provide accurate and indicative summaries of documents by taking the documents and creating distinctive abstracts from them. The products reviewed are: Oracle's ConText; InText's Object Analyzer; Iconovex's AnchorPage; and Software Scientific's Interrogator. Techniques used by the products include: the use of dictionaries of known words and phrases to interpret documents; and heuristic analysis involving weighting all the words in the document solely on their occurrence and position within the document
  5. Gomez, J.; Allen, K.; Matney, M.; Awopetu, T.; Shafer, S.: Experimenting with a machine generated annotations pipeline (2020) 0.02 
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    Abstract
    The UCLA Library reorganized its software developers into focused subteams with one, the Labs Team, dedicated to conducting experiments. In this article we describe our first attempt at conducting a software development experiment, in which we attempted to improve our digital library's search results with metadata from cloud-based image tagging services. We explore the findings and discuss the lessons learned from our first attempt at running an experiment.
  6. Jones, P.A.; Bradbeer, P.V.G.: Discovery of optimal weights in a concept selection system (1996) 0.02 
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    Source
    Information retrieval: new systems and current research. Proceedings of the 16th Research Colloquium of the British Computer Society Information Retrieval Specialist Group, Drymen, Scotland, 22-23 Mar 94. Ed.: R. Leon
  7. Craven, T.C.: ¬An experiment in the use of tools for computer-assisted abstracting (1996) 0.01 
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    Abstract
    Experimental subjects wrote abstracts of an article using a simplified version of the TEXNET abstracting assistance software. In addition to the fulltext, the 35 subjects were presented with either keywords or phrases extracted automatically. The resulting abstracts, and the times taken, were recorded automatically; some additional information was gathered by oral questionnaire. Results showed considerable variation among subjects, but 37% found the keywords or phrases quite or very useful in writing their abstracts. Statistical analysis failed to support deveral hypothesised relations; phrases were not viewed as significantly more helpful than keywords; and abstracting experience did not correlate with originality of wording, approximation of the author abstract, or greater conciseness. Results also suggested possible modifications to the software
  8. Craven, T.C.: Abstracts produced using computer assistance (2000) 0.01 
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    Abstract
    Experimental subjects wrote abstracts using a simplified version of the TEXNET abstracting assistance software. In addition to the full text, subjects were presented with either keywords or phrases extracted automatically. The resulting abstracts, and the times taken, were recorded automatically; some additional information was gathered by oral questionnaire. Selected abstracts produced were evaluated on various criteria by independent raters. Results showed considerable variation among subjects, but 37% found the keywords or phrases 'quite' or 'very' useful in writing their abstracts. Statistical analysis failed to support several hypothesized relations: phrases were not viewed as significantly more helpful than keywords; and abstracting experience did not correlate with originality of wording, approximation of the author abstract, or greater conciseness. Requiring further study are some unanticipated strong correlations including the following: Windows experience and writing an abstract like the author's; experience reading abstracts and thinking one had written a good abstract; gender and abstract length; gender and use of words and phrases from the original text. Results have also suggested possible modifications to the TEXNET software
  9. Su, H.: Automatic abstracting (1996) 0.01 
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    Date
    13. 5.1996 21:43:23
  10. Xianghao, G.; Yixin, Z.; Li, Y.: ¬A new method of news test understanding and abstracting based on speech acts theory (1998) 0.01 
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    Date
    13. 5.1996 21:43:23
  11. Dammeyer, A.; Jürgensen, W.; Krüwel, C.; Poliak, E.; Ruttkowski, S.; Schäfer, Th.; Sirava, M.; Hermes, T.: Videoanalyse mit DiVA (1998) 0.01 
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    Abstract
    Die Bedeutung von Videos nimmt für multimediale Systeme stetig zu. Dabei existiert eine Vielzahl von Produkten zur Betrachtung von Videos, allerdings nur wenige Ansätze, den Inhalt eines Videos zu erschließen. Das DiVA-System, welches an der Universität Bremen im Rahmen eines studentischen Projektes entwickelt wird, dient der automatischen Analyse von MPEG-I Videofilmen. Der dabei verfolgte Ansatz läßt sich in vier Phasen gliedern. Zunächst wird der Videofilm durch eine Shotanalyse in seine einzelnen Kameraeinstellungen (Shots) unterteilt. Darauf aufbauend findet eine Kamerabewegungsanalyse sowie die Erstellung von Mosaicbildern statt. Mit Methoden der künstlichen Intelligenz und der digitalen Bildverarbeitung wird das analysierte Material nach Bild- und Toninformationen ausgewertet. Das Resultat ist eine textuelle Beschreibung eines Videofilms, auf der mit Hilfe von Text-Retrieval-Systemen recherchiert werden kann
    Imprint
    Bremen : Universität Bremen / Fachbereich Mathematik und Informatik
    Source
    Inhaltsbezogene Suche von Bildern und Videosequenzen in digitalen multimedialen Archiven: Beiträge eines Workshops der KI'98 am 16./17.9.1998 in Bremen. Hrsg.: N. Luth
  12. Lee, J.-H.; Park, S.; Ahn, C.-M.; Kim, D.: Automatic generic document summarization based on non-negative matrix factorization (2009) 0.01 
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    Date
    23. 3.2013 13:24:19
  13. Sparck Jones, K.: Automatic summarising : the state of the art (2007) 0.01 
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    26.12.2007 14:40:23
  14. Díaz, A.; Gervás, P.: User-model based personalized summarization (2007) 0.01 
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    26.12.2007 16:27:23
  15. Pinto, M.: Engineering the production of meta-information : the abstracting concern (2003) 0.01 
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    Date
    27.11.2005 18:29:55
    Source
    Journal of information science. 29(2003) no.5, S.405-418
  16. Craven, T.C.: Presentation of repeated phrases in a computer-assisted abstracting tool kit (2001) 0.01 
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    Information processing and management. 37(2001) no.2, S.221-230
  17. Dunlavy, D.M.; O'Leary, D.P.; Conroy, J.M.; Schlesinger, J.D.: QCS: A system for querying, clustering and summarizing documents (2007) 0.01 
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    Abstract
    Information retrieval systems consist of many complicated components. Research and development of such systems is often hampered by the difficulty in evaluating how each particular component would behave across multiple systems. We present a novel integrated information retrieval system-the Query, Cluster, Summarize (QCS) system-which is portable, modular, and permits experimentation with different instantiations of each of the constituent text analysis components. Most importantly, the combination of the three types of methods in the QCS design improves retrievals by providing users more focused information organized by topic. We demonstrate the improved performance by a series of experiments using standard test sets from the Document Understanding Conferences (DUC) as measured by the best known automatic metric for summarization system evaluation, ROUGE. Although the DUC data and evaluations were originally designed to test multidocument summarization, we developed a framework to extend it to the task of evaluation for each of the three components: query, clustering, and summarization. Under this framework, we then demonstrate that the QCS system (end-to-end) achieves performance as good as or better than the best summarization engines. Given a query, QCS retrieves relevant documents, separates the retrieved documents into topic clusters, and creates a single summary for each cluster. In the current implementation, Latent Semantic Indexing is used for retrieval, generalized spherical k-means is used for the document clustering, and a method coupling sentence "trimming" and a hidden Markov model, followed by a pivoted QR decomposition, is used to create a single extract summary for each cluster. The user interface is designed to provide access to detailed information in a compact and useful format. Our system demonstrates the feasibility of assembling an effective IR system from existing software libraries, the usefulness of the modularity of the design, and the value of this particular combination of modules.
  18. Kuhlen, R.: Abstracts, abstracting : intellektuelle und maschinelle Verfahren (1990) 0.00 
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    Source
    Grundlagen der praktischen Information und Dokumentation. 3. Aufl. Hrsg.: M. Buder u.a. Bd.1
  19. Endres-Niggemeyer, B.: Bessere Information durch Zusammenfassen aus dem WWW (1999) 0.00 
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    Abstract
    Am Beispiel der Knochenmarktransplantation, eines medizinischen Spezialgebietes, wird im folgenden dargelegt, wie man BenutzerInnen eine großen Teil des Aufwandes bei der Wissensbeschaffung abnehmen kann, indem man Suchergebnisse aus dem Netz fragebezogen zusammenfaßt. Dadurch wird in zeitkritischen Situationen, wie sie in Diagnose und Therapie alltäglich sind, die Aufnahme neuen Wissens ermöglicht. Auf einen Überblick über den Stand des Textzusammenfassens und der Ontologieentwicklung folgt eine Systemskizze, in der die Informationssuche im WWW durch ein kognitiv fundiertes Zusammenfassungssystem ergänzt wird. Dazu wird eine Fach-Ontologie vorgeschlagen, die das benötigte Wissen organisiert und repräsentiert.
  20. Kuhlen, R.: Abstracts, abstracting : intellektuelle und maschinelle Verfahren (1997) 0.00 
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    Source
    Grundlagen der praktischen Information und Dokumentation: ein Handbuch zur Einführung in die fachliche Informationsarbeit. 4. Aufl. Hrsg.: M. Buder u.a

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