Search (24 results, page 1 of 2)

  • × year_i:[1980 TO 1990}
  • × theme_ss:"Computerlinguistik"
  1. Schwarz, C.: THESYS: Thesaurus Syntax System : a fully automatic thesaurus building aid (1988) 0.02
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    Abstract
    THESYS is based on the natural language processing of free-text databases. It yields statistically evaluated correlations between words of the database. These correlations correspond to traditional thesaurus relations. The person who has to build a thesaurus is thus assisted by the proposals made by THESYS. THESYS is being tested on commercial databases under real world conditions. It is part of a text processing project at Siemens, called TINA (Text-Inhalts-Analyse). Software from TINA is actually being applied and evaluated by the US Department of Commerce for patent search and indexing (REALIST: REtrieval Aids by Linguistics and STatistics)
    Date
    6. 1.1999 10:22:07
  2. Sparck Jones, K.: Synonymy and semantic classification (1986) 0.02
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  3. Wenzel, F.: Semantische Eingrenzung im Freitext-Retrieval auf der Basis morphologischer Segmentierungen (1980) 0.02
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    Abstract
    The basic problem in freetext retrieval is that the retrieval language is not properly adapted to that of the author. Morphological segmentation, where words with the same root are grouped together in the inverted file, is a good eliminator of noise and information loss, providing high recall but low precision
  4. McCune, B.P.; Tong, R.M.; Dean, J.S.: Rubric: a system for rule-based information retrieval (1985) 0.02
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    Footnote
    Wiederabgedruckt in: Readings in information retrieval. Ed.: K. Sparck Jones u. P. Willett. San Francisco: Morgan Kaufmann 1997. S.440-445.
  5. Schwarz, C.: Linguistische Hilfsmittel beim Information Retrieval (1984) 0.01
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  6. Metzler, D.P.; Haas, S.W.: ¬The constituent object parser : syntactic structure matching for information retrieval (1989) 0.01
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    Abstract
    The constituent object parser is designed to improve the precision and recall performance of information retrieval by providing more powerful matching procedures. Describes the dependency tree representations and the relationship between the intended use of the parser and its design.
  7. Rau, L.F.: Conceptual information extraction and retrieval from natural language input (198) 0.01
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    Footnote
    Wiederabgedruckt in: Readings in information retrieval. Ed.: K. Sparck Jones u. P. Willett. San Francisco: Morgan Kaufmann 1997. S.527-533
  8. Schwarz, C.: Natural language and information retrieval : Kommentierte Literaturliste zu Systemen, Verfahren und Tools (1986) 0.01
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  9. Rau, L.F.; Jacobs, P.S.; Zernik, U.: Information extraction and text summarization using linguistic knowledge acquisition (1989) 0.01
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    Abstract
    Storing and accessing texts in a conceptual format has a number of advantages over traditional document retrieval methods. A conceptual format facilitates natural language access to text information. It can support imprecise and inexact queries, conceptual information summarisation, and, ultimately, document translation. Describes 2 methods which have been implemented in a prototype intelligent information retrieval system calles SCISOR (System for Conceptual Information Summarisation, Organization and Retrieval). Describes the text processing, language acquisition, and summarisation components of SCISOR
  10. Informationslinguistische Texterschließung (1986) 0.01
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    LCSH
    Information storage and retrieval systems / Linguistics
    RSWK
    Information Retrieval / Aufsatzsammlung (DNB)
    Linguistik / Information Retrieval / Aufsatzsammlung (SWB / BVB)
    Subject
    Information Retrieval / Aufsatzsammlung (DNB)
    Linguistik / Information Retrieval / Aufsatzsammlung (SWB / BVB)
    Information storage and retrieval systems / Linguistics
  11. Porter, M.F.: ¬An algorithm for suffix stripping (1980) 0.01
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    Footnote
    Wiederabgedruckt in: Readings in information retrieval. Ed.: K. Sparck Jones u. P. Willett. San Francisco: Morgan Kaufmann 1997. S.313-316.
  12. Metzler, D.P.; Haas, S.W.; Cosic, C.L.; Wheeler, L.H.: Constituent object parsing for information retrieval and similar text processing problems (1989) 0.01
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    Abstract
    Describes the architecture and functioning of the Constituent Object Parser. This system has been developed specially for text processing applications such as information retrieval, which can benefit from structural comparisons between elements of text such as a query and a potentially relevant abstract. Describes the general way in which this objective influenced the design of the system.
  13. Warner, A.J.: Natural language processing (1987) 0.01
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    Source
    Annual review of information science and technology. 22(1987), S.79-108
  14. Salton, G.: Automatic processing of foreign language documents (1985) 0.01
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    Abstract
    The attempt to computerize a process, such as indexing, abstracting, classifying, or retrieving information, begins with an analysis of the process into its intellectual and nonintellectual components. That part of the process which is amenable to computerization is mechanical or algorithmic. What is not is intellectual or creative and requires human intervention. Gerard Salton has been an innovator, experimenter, and promoter in the area of mechanized information systems since the early 1960s. He has been particularly ingenious at analyzing the process of information retrieval into its algorithmic components. He received a doctorate in applied mathematics from Harvard University before moving to the computer science department at Cornell, where he developed a prototype automatic retrieval system called SMART. Working with this system he and his students contributed for over a decade to our theoretical understanding of the retrieval process. On a more practical level, they have contributed design criteria for operating retrieval systems. The following selection presents one of the early descriptions of the SMART system; it is valuable as it shows the direction automatic retrieval methods were to take beyond simple word-matching techniques. These include various word normalization techniques to improve recall, for instance, the separation of words into stems and affixes; the correlation and clustering, using statistical association measures, of related terms; and the identification, using a concept thesaurus, of synonymous, broader, narrower, and sibling terms. They include, as weIl, techniques, both linguistic and statistical, to deal with the thorny problem of how to automatically extract from texts index terms that consist of more than one word. They include weighting techniques and various documentrequest matching algorithms. Significant among the latter are those which produce a retrieval output of citations ranked in relevante order. During the 1970s, Salton and his students went an to further refine these various techniques, particularly the weighting and statistical association measures. Many of their early innovations seem commonplace today. Some of their later techniques are still ahead of their time and await technological developments for implementation. The particular focus of the selection that follows is an the evaluation of a particular component of the SMART system, a multilingual thesaurus. By mapping English language expressions and their German equivalents to a common concept number, the thesaurus permitted the automatic processing of German language documents against English language queries and vice versa. The results of the evaluation, as it turned out, were somewhat inconclusive. However, this SMART experiment suggested in a bold and optimistic way how one might proceed to answer such complex questions as What is meant by retrieval language compatability? How it is to be achieved, and how evaluated?
  15. Gerstenkorn, A.: Indexierung mit Nominalgruppen (1980) 0.01
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    Abstract
    Die Indexierung mit Nominalgruppen ist eine konsequente Fortsetzung der Entwicklung von der gleichordnenden zur syntaktischen Indexierung. Nominalgruppen eignen sich besonders zur Bezeichnung komplexer Begriffe (Themen) und sind benutzerfreundlich. Bei einer automatischen Indexierung mit Nominalgruppen sind keine vollständigen Satzanalysen nötig, auch Systeme mit einem partiellen Parser liefern brauchbare Ergebnisse. Das Problem eines Retrieval mit Nominalgruppen ist noch zu lösen
  16. Hayes, P.J.; Knecht, L.E.; Cellio, M.J.: ¬A news story categorization system (1988) 0.01
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    Footnote
    Wiederabgedruckt in: Readings in information retrieval. Ed.: K. Sparck Jones u. P. Willett. San Francisco: Morgan Kaufmann 1997. S.518-526
  17. Stock, M.: Textwortmethode und Übersetzungsrelation : Eine Methode zum Aufbau von kombinierten Literaturnachweis- und Terminologiedatenbanken (1989) 0.01
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    Abstract
    Geisteswissenschaftliche Fachinformation erfordert eine enge Kooperation zwischen Literaturnachweis- und Terminologieinformationssystemen. Eine geeignete Dokumentationsmethode für die Auswertung geisteswissen- schaftlicher Literatur ist die Textwortwethode. Dem originalsprachig aufgenommenen Begriffsrepertoire ist ein einheitssprachiger Zugriff beizuordnen, der einerseits ein vollständiges und genaues Retrieval garantiert und andererseits den Aufbau fachspezifischer Wörterbücher vorantreibt
  18. Fagan, J.L.: ¬The effectiveness of a nonsyntactic approach to automatic phrase indexing for document retrieval (1989) 0.01
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    Abstract
    It may be possible to improve the quality of automatic indexing systems by using complex descriptors, for example, phrases, in addition to the simple descriptors (words or word stems) that are normally used in automatically constructed representations of document content. This study is directed toward the goal of developing effective methods of identifying phrases in natural language text from which good quality phrase descriptors can be constructed. The effectiveness of one method, a simple nonsyntactic phrase indexing procedure, has been tested on five experimental document collections. The results have been analyzed in order to identify the inadequacies of the procedure, and to determine what kinds of information about text structure are needed in order to construct phrase descriptors that are good indicators of document content. Two primary conclusions have been reached: (1) In the retrieval experiments, the nonsyntactic phrase construction procedure did not consistently yield substantial improvements in effectiveness. It is therefore not likely that phrase indexing of this kind will prove to be an important method of enhancing the performance of automatic document indexing and retrieval systems in operational environments. (2) Many of the shortcomings of the nonsyntactic approach can be overcome by incorporating syntactic information into the phrase construction process. However, a general syntactic analysis facility may be required, since many useful sources of phrases cannot be exploited if only a limited inventory of syntactic patterns can be recognized. Further research should be conducted into methods of incorporating automatic syntactic analysis into content analysis for document retrieval.
  19. Hahn, U.: Informationslinguistik : I: Einführung in das linguistische Information Retrieval (1985) 0.01
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    Abstract
    (1) "Informationslinguistik I: Einfuehrung in das linguistische Information Retrieval" (2) "Informationslinguistik II: linguistische und statistische Verfahren im experimentellen Information Retrieval" (3) "Intelligente Informationssysteme: Verfahren der Kuenstlichen Intelligenz im experimentellen Information Retrieval" Kursabschnitt zu natuerlichsprachlichen Systemen (4) Spezialkurse zum automatischen Uebersetzen, Indexing und Retrieval, Abstracting usf. dienen zur Vertiefung informationslinguistischer Spezialthemen Die Kurse (1) und (3) gehoeren zu dem Pool der Pflichtveranstaltungen aller Studenten des Diplom-Studiengangs Informationswissenschaft, waehrend (2) und (4) lediglich zu den Wahlpflichtveranstaltungen zaehlen, die aber obligatorisch fuer die Studenten des Diplomstudiengangs sind, die ihren Schwerpunkt (z.B. in Form der Diplomarbeit) im Bereich Informationslinguistik suchen - fuer alle anderen Studenten zaehlen diese Kurse zum Zusatz angebot an Lehrveranstaltungen.
    Content
    2. Teil u.d.T.: Linguistische und statistische Verfahren im experimentellen Information Retrieval
  20. Hahn, U.: Informationslinguistik : II: Einführung in das linguistische Information Retrieval (1985) 0.01
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    Abstract
    (1) "Informationslinguistik I: Einfuehrung in das linguistische Information Retrieval" (2) "Informationslinguistik II: linguistische und statistische Verfahren im experimentellen Information Retrieval" (3) "Intelligente Informationssysteme: Verfahren der Kuenstlichen Intelligenz im experimentellen Information Retrieval" Kursabschnitt zu natuerlichsprachlichen Systemen (4) Spezialkurse zum automatischen Uebersetzen, Indexing und Retrieval, Abstracting usf. dienen zur Vertiefung informationslinguistischer Spezialthemen Die Kurse (1) und (3) gehoeren zu dem Pool der Pflichtveranstaltungen aller Studenten des Diplom-Studiengangs Informationswissenschaft, waehrend (2) und (4) lediglich zu den Wahlpflichtveranstaltungen zaehlen, die aber obligatorisch fuer die Studenten des Diplomstudiengangs sind, die ihren Schwerpunkt (z.B. in Form der Diplomarbeit) im Bereich Informationslinguistik suchen - fuer alle anderen Studenten zaehlen diese Kurse zum Zusatz angebot an Lehrveranstaltungen.
    Das vorliegende Skript entspricht dem Inhalt des Kurses "Informationslinguistik II" im SS 1983 bzw. SS 1984. Es ist im Juli 1983 inhaltlich abgeschlossen und im Januar 1985 lediglich redaktionell ueberarbeitet worden. Die Erstellung des Skripts entspricht einem dezidierten Auftrag des Projekts "Informationsvermittlung", der die Entwicklung geeigneter Lehrmaterialien zum informationswissenschaftlichen Aufbaustudium vorsah. Aufgrund des engen Projektzeitrahmens (1982-84) kann das Skript nicht in dem Masse voll ausgereift und ausformuliert sein, wie es gaengigen Standards entspraeche. Im Unterschied zum Skript "Informationslinguistik I" (HAHN 1985) laesst das vorliegende Skript wahlweise eine eher methoden- oder mehr systembezogene Darstellung informationslinguistischer Konzepte des experimentellen Information Retrieval zu (beides zusammen schliesst der enge Zeitrahmen eines Sommersemesters ausl). Die Entscheidung darueber sollte wenn moeglich in Abhaengigkeit zur personellen Zusammensetzung des Kurses getroffen werden, wobei - sofern die bislang genachten Erfahrungen verallgemeinerbar sind - sich bei einem nicht ausschliesslich an einer informationslinguistischen Spezialisierung interessierten und damit heterogenen Publikum die mehr systembezogene Praesentation als fuer das Verstaendnis informationslinguistischer Fragestellungen und entsprechender Verfahrensloesungen guenstiger gezeigt hat. Innerhalb dieser Nuancierung besitzt aber auch dieses Skript schon eine akzeptable inhaltliche Stabilitaet. Nichtsdestotrotz sollte gerade die Veroeffentlichung des Skripts als Anregung dienen, kritische Kommentare, Anmerkungen und Ergaenzungen zu diesem curricularen Entwurf herauszufordern, um damit die weitere disziplinaere Klaerung der Informationslinguistik zu foerdern.
    Content
    1. Teil u.d.T.: Einführung in das linguistische Information Retrieval

Languages

  • e 15
  • d 9

Types

  • a 20
  • m 4
  • s 1
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