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Lutz-Westphal, B.: ChatGPT und der "Faktor Mensch" im schulischen Mathematikunterricht (2023)
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- Field
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-
Hartnett, K.: Sind Sprachmodelle bald die besseren Mathematiker? (2023)
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- Field
- Mathematik
-
Scobel, G.: GPT: Eine Software, die die Welt verändert (2023)
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- Date
- 23. 1.2023 17:28:51
- Source
- https://www.zdf.de/nachrichten/panorama/gpt-ki-literatur-terrax-gert-scobel-kolumne-100.html?utm_source=pocket-newtab-global-de-DE
-
Schöneberg, U.; Sperber, W.: POS tagging and its applications for mathematics (2014)
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- Field
- Mathematik
- Object
- Zentralblatt für Mathematik
-
Strube, M.: Kreativ durch Analogien (2011)
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- Content
- "Die Computerlinguistik vereinigt Elemente von Informatik und Linguistik; sie verwendet darüber hinaus Methoden aus weiteren Gebieten wie Mathematik, Psychologie, Statistik und künstliche Intelligenz. Der Reiz und die Herausforderung einer solchen interdisziplinären Wissenschaft liegen darin, Analogien zwischen Konzepten aus weit entfernten Teilgebieten zu erkennen und zu nutzen. Paradebeispiel dafür ist einer der entscheidenden Durchbrüche, welche die Computerlinguistik prägten. Es geht um das »Parsing«: Ein Computerprogramm, genauer gesagt ein Compiler, nimmt Zeichen für Zeichen den Input des Benutzers entgegen, der in diesem Fall seinerseits aus dem Text eines Computerprogramms besteht, und ermittelt dessen Struktur. Im Prinzip dasselbe tut ein Mensch, der einen gesprochenen Satz hört und versteht."
-
Stoykova, V.; Petkova, E.: Automatic extraction of mathematical terms for precalculus (2012)
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- Field
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Aizawa, A.; Kohlhase, M.: Mathematical information retrieval (2021)
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- Field
- Mathematik
-
Collard, J.; Paiva, V. de; Fong, B.; Subrahmanian, E.: Extracting mathematical concepts from text (2022)
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Hull, D.; Ait-Mokhtar, S.; Chuat, M.; Eisele, A.; Gaussier, E.; Grefenstette, G.; Isabelle, P.; Samulesson, C.; Segand, F.: Language technologies and patent search and classification (2001)
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- Source
- World patent information. 23(2001), S.265-268
-
Schank, R.C.: Conceptual information processing (1975)
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- Date
- 17.10.1996 10:23:33
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Fellbaum, C.: ¬A semantic network of English : the mother of all WordNets (1998)
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- Date
- 10. 8.2001 21:23:23
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Witschel, H.F.: Text, Wörter, Morpheme : Möglichkeiten einer automatischen Terminologie-Extraktion (2004)
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- Imprint
- Leipzig : Universität / Fakultät für Mathematik und Informatik Institut für Informatik
-
Endres-Niggemeyer, B.: Sprachverarbeitung im Informationsbereich (1989)
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- Pages
- S.9-23
-
Sager, N.: Natural language information processing (1981)
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- Date
- 17.10.1996 10:19:23
-
Schank, R.C.; Abelson, R.P.: Sripts, plans, goals, and understanding (1977)
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- Date
- 17.10.1996 10:23:33
-
Rötzer, F.: Computer ergooglen die Bedeutung von Worten (2005)
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- Content
- "Wie könnten Computer Sprache lernen und dabei auch die Bedeutung von Worten sowie die Beziehungen zwischen ihnen verstehen? Dieses Problem der Semantik stellt eine gewaltige, bislang nur ansatzweise bewältigte Aufgabe dar, da Worte und Wortverbindungen oft mehrere oder auch viele Bedeutungen haben, die zudem vom außersprachlichen Kontext abhängen. Die beiden holländischen (Ein künstliches Bewusstsein aus einfachen Aussagen (1)). Paul Vitanyi (2) und Rudi Cilibrasi vom Nationalen Institut für Mathematik und Informatik (3) in Amsterdam schlagen eine elegante Lösung vor: zum Nachschlagen im Internet, der größten Datenbank, die es gibt, wird einfach Google benutzt. Objekte wie eine Maus können mit ihren Namen "Maus" benannt werden, die Bedeutung allgemeiner Begriffe muss aus ihrem Kontext gelernt werden. Ein semantisches Web zur Repräsentation von Wissen besteht aus den möglichen Verbindungen, die Objekte und ihre Namen eingehen können. Natürlich können in der Wirklichkeit neue Namen, aber auch neue Bedeutungen und damit neue Verknüpfungen geschaffen werden. Sprache ist lebendig und flexibel. Um einer Künstlichen Intelligenz alle Wortbedeutungen beizubringen, müsste mit der Hilfe von menschlichen Experten oder auch vielen Mitarbeitern eine riesige Datenbank mit den möglichen semantischen Netzen aufgebaut und dazu noch ständig aktualisiert werden. Das aber müsste gar nicht notwendig sein, denn mit dem Web gibt es nicht nur die größte und weitgehend kostenlos benutzbare semantische Datenbank, sie wird auch ständig von zahllosen Internetnutzern aktualisiert. Zudem gibt es Suchmaschinen wie Google, die Verbindungen zwischen Worten und damit deren Bedeutungskontext in der Praxis in ihrer Wahrscheinlichkeit quantitativ mit der Angabe der Webseiten, auf denen sie gefunden wurden, messen.
-
Kiss, T.: Anmerkungen zur scheinbaren Konkurrenz von numerischen und symbolischen Verfahren in der Computerlinguistik (2002)
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- Abstract
- Man kann wohl abschließend festhalten, dass von einer Überlegenheit statistischer Verfahren zumindest im Bereich des Tagging eigentlich nicht gesprochen werden sollte. Darüber hinaus muss die Opposition zwischen regelbasierten und numerischen Verfahren hier aufgeweicht werden, denn auch die statistischen Verfahren verwenden Regelsysteme. Selbst beim Lernen ohne Referenzkorpus ist ja zumindest eine Zuordnung der Wörter zu einem Lexikon bzw. auch eine heuristische Erkennung unbekannter Wörter nach Regeln notwendig. Statistische Verfahren haben - und dies wurde hier wahrscheinlich nicht ausreichend betont - durchaus ihre Berechtigung, sie sind nützlich; sie gestatten, insbesondere im Vergleich zur Introspektion, eine unmittelbarere und breitere Heranführung an das Phänomen Sprache. Die vorhandenen umfangreichen elektronischen Korpora verlangen nahezu danach, Sprache auch mit statistischen Mitteln zu untersuchen. Allerdings können die statistischen Verfahren die regelbasierten Verfahren nicht ersetzen. Somit muss dem Diktum vom "Es geht nicht anders" deutlich widersprochen werden. Dass die statistischen Verfahren zur Zeit so en vogue sind und die regelbasierten Verfahren aussehen lassen wie eine alte Dallas-Folge, mag wohl auch daran liegen, dass zu viele Vertreter des alten Paradigmas nicht die Energie aufbringen, sich dem neuen Paradigma so weit zu öffnen, dass eine kritische Auseinandersetzung mit dem neuen auf der Basis des alten möglich wird. Die Mathematik ist eine geachtete, weil schwierige Wissenschaft, die statistische Sprachverarbeitung ist eine gefürchtete, weil in ihren Eigenschaften oftmals nicht gründlich genug betrachtete Disziplin.
-
Sheridan, P.; Smeaton, A.F.: ¬The application of morpho-syntactic language processing to effective phrase matching (1992)
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- Date
- 8.10.2000 15:02:23
-
Dietze, J.: Texterschließung : lexikalische Semantik und Wissensrepräsentation (1994)
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- Footnote
- Rez.in: Knowledge organization 23(1996) no.2, S.116 (E. Mater)
-
Building lexicons for machine translation (1994/95)
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- Date
- 18. 5.1996 16:23:54
