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Hotho, A.; Bloehdorn, S.: Data Mining 2004 : Text classification by boosting weak learners based on terms and concepts (2004)
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- 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.
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- 8. 1.2013 10:22:32
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Noever, D.; Ciolino, M.: ¬The Turing deception (2022)
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- https%3A%2F%2Farxiv.org%2Fabs%2F2212.06721&usg=AOvVaw3i_9pZm9y_dQWoHi6uv0EN
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¬Der Student aus dem Computer (2023)
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- Date
- 27. 1.2023 16:22:55
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Monnerjahn, P.: Vorsprung ohne Technik : Übersetzen: Computer und Qualität (2000)
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- c't. 2000, H.22, S.230-231
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Lezius, W.; Rapp, R.; Wettler, M.: ¬A morphology-system and part-of-speech tagger for German (1996)
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- Date
- 22. 3.2015 9:37:18
- Language
- d
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- Natural language processing and speech technology: Results of the 3rd KONVENS Conference, Bielefeld, October 1996. Ed.: D. Gibbon
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Kuhlmann, U.; Monnerjahn, P.: Sprache auf Knopfdruck : Sieben automatische Übersetzungsprogramme im Test (2000)
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Deventer, J.P. van; Kruger, C.J.; Johnson, R.D.: Delineating knowledge management through lexical analysis : a retrospective (2015)
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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
-
Ruge, G.: Sprache und Computer : Wortbedeutung und Termassoziation. Methoden zur automatischen semantischen Klassifikation (1995)
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- Footnote
- Rez. in: Knowledge organization 22(1995) no.3/4, S.182-184 (M.T. Rolland)
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- d
- Type
- d
-
Lezius, W.: Morphy - Morphologie und Tagging für das Deutsche (2013)
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- Date
- 22. 3.2015 9:30:24
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- d
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Bager, J.: ¬Die Text-KI ChatGPT schreibt Fachtexte, Prosa, Gedichte und Programmcode (2023)
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- Date
- 29.12.2022 18:22:55
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- d
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Rieger, F.: Lügende Computer (2023)
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- 16. 3.2023 19:22:55
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Schneider, R.: Web 3.0 ante portas? : Integration von Social Web und Semantic Web (2008)
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- Date
- 22. 1.2011 10:38:28
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Warner, A.J.: Natural language processing (1987)
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- Annual review of information science and technology. 22(1987), S.79-108
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Lorenz, S.: Konzeption und prototypische Realisierung einer begriffsbasierten Texterschließung (2006)
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- 22. 3.2015 9:17:30
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Lawrie, D.; Mayfield, J.; McNamee, P.; Oard, P.W.: Cross-language person-entity linking from 20 languages (2015)
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- Abstract
- The goal of entity linking is to associate references to an entity that is found in unstructured natural language content to an authoritative inventory of known entities. This article describes the construction of 6 test collections for cross-language person-entity linking that together span 22 languages. Fully automated components were used together with 2 crowdsourced validation stages to affordably generate ground-truth annotations with an accuracy comparable to that of a completely manual process. The resulting test collections each contain between 642 (Arabic) and 2,361 (Romanian) person references in non-English texts for which the correct resolution in English Wikipedia is known, plus a similar number of references for which no correct resolution into English Wikipedia is believed to exist. Fully automated cross-language person-name linking experiments with 20 non-English languages yielded a resolution accuracy of between 0.84 (Serbian) and 0.98 (Romanian), which compares favorably with previously reported cross-language entity linking results for Spanish.
-
Levin, M.; Krawczyk, S.; Bethard, S.; Jurafsky, D.: Citation-based bootstrapping for large-scale author disambiguation (2012)
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- Abstract
- We present a new, two-stage, self-supervised algorithm for author disambiguation in large bibliographic databases. In the first "bootstrap" stage, a collection of high-precision features is used to bootstrap a training set with positive and negative examples of coreferring authors. A supervised feature-based classifier is then trained on the bootstrap clusters and used to cluster the authors in a larger unlabeled dataset. Our self-supervised approach shares the advantages of unsupervised approaches (no need for expensive hand labels) as well as supervised approaches (a rich set of features that can be discriminatively trained). The algorithm disambiguates 54,000,000 author instances in Thomson Reuters' Web of Knowledge with B3 F1 of.807. We analyze parameters and features, particularly those from citation networks, which have not been deeply investigated in author disambiguation. The most important citation feature is self-citation, which can be approximated without expensive extraction of the full network. For the supervised stage, the minor improvement due to other citation features (increasing F1 from.748 to.767) suggests they may not be worth the trouble of extracting from databases that don't already have them. A lean feature set without expensive abstract and title features performs 130 times faster with about equal F1.
-
Sienel, J.; Weiss, M.; Laube, M.: Sprachtechnologien für die Informationsgesellschaft des 21. Jahrhunderts (2000)
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- Date
- 26.12.2000 13:22:17
- Language
- d
- Source
- Sprachtechnologie für eine dynamische Wirtschaft im Medienzeitalter - Language technologies for dynamic business in the age of the media - L'ingénierie linguistique au service de la dynamisation économique à l'ère du multimédia: Tagungsakten der XXVI. Jahrestagung der Internationalen Vereinigung Sprache und Wirtschaft e.V., 23.-25.11.2000, Fachhochschule Köln. Hrsg.: K.-D. Schmitz
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McMahon, J.G.; Smith, F.J.: Improved statistical language model performance with automatic generated word hierarchies (1996)
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- Source
- Computational linguistics. 22(1996) no.2, S.217-248
-
Ruge, G.: ¬A spreading activation network for automatic generation of thesaurus relationships (1991)
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- Date
- 8.10.2000 11:52:22
-
Somers, H.: Example-based machine translation : Review article (1999)
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- Date
- 31. 7.1996 9:22:19
