Search (81 results, page 1 of 5)

  • × theme_ss:"Computerlinguistik"
  1. Hotho, A.; Bloehdorn, S.: Data Mining 2004 : Text classification by boosting weak learners based on terms and concepts (2004) 0.07
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    Content
    Vgl.: http://www.google.de/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&ved=0CEAQFjAA&url=http%3A%2F%2Fciteseerx.ist.psu.edu%2Fviewdoc%2Fdownload%3Fdoi%3D10.1.1.91.4940%26rep%3Drep1%26type%3Dpdf&ei=dOXrUMeIDYHDtQahsIGACg&usg=AFQjCNHFWVh6gNPvnOrOS9R3rkrXCNVD-A&sig2=5I2F5evRfMnsttSgFF9g7Q&bvm=bv.1357316858,d.Yms.
    Date
    8. 1.2013 10:22:32
  2. Lorenz, S.: Konzeption und prototypische Realisierung einer begriffsbasierten Texterschließung (2006) 0.06
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    Content
    Dissertation an der Universität Trier - Fachbereich IV - zur Erlangung der Würde eines Doktors der Wirtschafts- und Sozialwissenschaften. Vgl.: http://ubt.opus.hbz-nrw.de/volltexte/2006/377/pdf/LorenzSaschaDiss.pdf.
    Date
    22. 3.2015 9:17:30
    Year
    2006
  3. Frobese, D.T.: Klassifikationsaufgaben mit der SENTRAX : Konkreter Fall: Automatische Detektion von SPAM (2006) 0.04
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    Footnote
    Beitrag der Proceedings des Fünften Hildesheimer Evaluierungs- und Retrievalworkshop (HIER 2006), Hildesheim, xx.x.2006.
    Source
    http://web1.bib.uni-hildesheim.de/edocs/2006/51992004X/doc/51992004X.pdf
    Year
    2006
  4. Deventer, J.P. van; Kruger, C.J.; Johnson, R.D.: Delineating knowledge management through lexical analysis : a retrospective (2015) 0.04
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    Abstract
    Purpose Academic authors tend to define terms that meet their own needs. Knowledge Management (KM) is a term that comes to mind and is examined in this study. Lexicographical research identified KM terms used by authors from 1996 to 2006 in academic outlets to define KM. Data were collected based on strict criteria which included that definitions should be unique instances. From 2006 onwards, these authors could not identify new unique instances of definitions with repetitive usage of such definition instances. Analysis revealed that KM is directly defined by People (Person and Organisation), Processes (Codify, Share, Leverage, and Process) and Contextualised Content (Information). The paper aims to discuss these issues. Design/methodology/approach The aim of this paper is to add to the body of knowledge in the KM discipline and supply KM practitioners and scholars with insight into what is commonly regarded to be KM so as to reignite the debate on what one could consider as KM. The lexicon used by KM scholars was evaluated though the application of lexicographical research methods as extended though Knowledge Discovery and Text Analysis methods. Findings By simplifying term relationships through the application of lexicographical research methods, as extended though Knowledge Discovery and Text Analysis methods, it was found that KM is directly defined by People (Person and Organisation), Processes (Codify, Share, Leverage, Process) and Contextualised Content (Information). One would therefore be able to indicate that KM, from an academic point of view, refers to people processing contextualised content.
    Research limitations/implications In total, 42 definitions were identified spanning a period of 11 years. This represented the first use of KM through the estimated apex of terms used. From 2006 onwards definitions were used in repetition, and all definitions that were considered to repeat were therefore subsequently excluded as not being unique instances. All definitions listed are by no means complete and exhaustive. The definitions are viewed outside the scope and context in which they were originally formulated and then used to review the key concepts in the definitions themselves. Social implications When the authors refer to the aforementioned discussion of KM content as well as the presentation of the method followed in this paper, the authors may have a few implications for future research in KM. First the research validates ideas presented by the OECD in 2005 pertaining to KM. It also validates that through the evolution of KM, the authors ended with a description of KM that may be seen as a standardised description. If the authors as academics and practitioners, for example, refer to KM as the same construct and/or idea, it has the potential to speculatively, distinguish between what KM may or may not be. Originality/value By simplifying the term used to define KM, by focusing on the most common definitions, the paper assist in refocusing KM by reconsidering the dimensions that is the most common in how it has been defined over time. This would hopefully assist in reigniting discussions about KM and how it may be used to the benefit of an organisation.
    Date
    20. 1.2015 18:30:22
  5. Kunze, C.: Lexikalisch-semantische Wortnetze in Sprachwissenschaft und Sprachtechnologie (2006) 0.03
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    Source
    Information - Wissenschaft und Praxis. 57(2006) H.6/7, S.309-314
    Year
    2006
  6. Koppel, M.; Akiva, N.; Dagan, I.: Feature instability as a criterion for selecting potential style markers (2006) 0.03
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    Source
    Journal of the American Society for Information Science and Technology. 57(2006) no.11, S.1519-1525
    Year
    2006
  7. Noever, D.; Ciolino, M.: ¬The Turing deception (2022) 0.03
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    Source
    https%3A%2F%2Farxiv.org%2Fabs%2F2212.06721&usg=AOvVaw3i_9pZm9y_dQWoHi6uv0EN
  8. Warner, A.J.: Natural language processing (1987) 0.02
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    Source
    Annual review of information science and technology. 22(1987), S.79-108
  9. Kummer, N.: Indexierungstechniken für das japanische Retrieval (2006) 0.02
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    Year
    2006
  10. Collins, C.: WordNet explorer : applying visualization principles to lexical semantics (2006) 0.02
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    Year
    2006
  11. Mustafa El Hadi, W.: Terminologies, ontologies and information access (2006) 0.02
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    Year
    2006
  12. Bubenhofer, N.: Einführung in die Korpuslinguistik : Praktische Grundlagen und Werkzeuge (2006) 0.02
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    Year
    2006
  13. Nhongkai, S.N.; Bentz, H.-J.: Bilinguale Suche mittels Konzeptnetzen (2006) 0.02
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    Year
    2006
  14. Duwairi, R.M.: Machine learning for Arabic text categorization (2006) 0.02
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    Source
    Journal of the American Society for Information Science and Technology. 57(2006) no.8, S.1005-1010
    Year
    2006
  15. Galvez, C.; Moya-Anegón, F. de: ¬An evaluation of conflation accuracy using finite-state transducers (2006) 0.02
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    Source
    Journal of documentation. 62(2006) no.3, S.328-349
    Year
    2006
  16. Navarretta, C.; Pedersen, B.S.; Hansen, D.H.: Language technology in knowledge-organization systems (2006) 0.02
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    Source
    New review of hypermedia and multimedia. 12(2006) no.1, S.29-49
    Year
    2006
  17. Thelwall, M.; Price, L.: Language evolution and the spread of ideas on the Web : a procedure for identifying emergent hybrid word (2006) 0.02
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    Source
    Journal of the American Society for Information Science and Technology. 57(2006) no.10, S.1326-1337
    Year
    2006
  18. Cimiano, P.; Völker, J.; Studer, R.: Ontologies on demand? : a description of the state-of-the-art, applications, challenges and trends for ontology learning from text (2006) 0.02
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    Source
    Information - Wissenschaft und Praxis. 57(2006) H.6/7, S.315-320
    Year
    2006
  19. Vechtomova, O.; Karamuftuoglum, M.; Robertson, S.E.: On document relevance and lexical cohesion between query terms (2006) 0.02
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    Source
    Information processing and management. 42(2006) no.5, S.1230-1247
    Year
    2006
  20. McMahon, J.G.; Smith, F.J.: Improved statistical language model performance with automatic generated word hierarchies (1996) 0.02
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    Source
    Computational linguistics. 22(1996) no.2, S.217-248

Years

Languages

  • e 53
  • d 28

Types

  • a 63
  • el 9
  • m 8
  • s 5
  • p 2
  • x 2
  • d 1
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