Search (21 results, page 1 of 2)

Hotho, A.; Bloehdorn, S.: Data Mining 2004 : Text classification by boosting weak learners based on terms and concepts (2004) 0.11

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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

Meder, N.: Artificial intelligence as a tool of classification, or: the network of language games as cognitive paradigm (1985) 0.04
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Abstract

It is shown that the cognitive paradigm may be an orientation mark for automatic classification. On the basis of research in Artificial Intelligence, the cognitive paradigm - as opposed to the behavioristic paradigm - was developed as a multiplicity of competitive world-views. This is the thesis of DeMey in his book "The cognitive paradigm". Multiplicity in a loosely-coupled network of cognitive knots is also the principle of dynamic restlessness. In competititon with cognitive views, a classification system that follows various models may learn by concrete information retrieval. During his actions the user builds implicitly a new classification order
Schek, M.: Automatische Klassifizierung in Erschließung und Recherche eines Pressearchivs (2006) 0.02
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Abstract

Die Süddeutsche Zeitung (SZ) verfügt seit ihrer Gründung 1945 über ein Pressearchiv, das die Texte der eigenen Redakteure und zahlreicher nationaler und internationaler Publikationen dokumentiert und für Recherchezwecke bereitstellt. Die DIZ-Pressedatenbank (www.medienport.de) ermöglicht die browserbasierte Recherche für Redakteure und externe Kunden im Intra- und Internet und die kundenspezifischen Content Feeds für Verlage, Rundfunkanstalten und Portale. Die DIZ-Pressedatenbank enthält z. Zt. 7,8 Millionen Artikel, die jeweils als HTML oder PDF abrufbar sind. Täglich kommen ca. 3.500 Artikel hinzu, von denen ca. 1.000 durch Dokumentare inhaltlich erschlossen werden. Die Informationserschließung erfolgt im DIZ nicht durch die Vergabe von Schlagwörtern am Dokument, sondern durch die Verlinkung der Artikel mit "virtuellen Mappen", den Dossiers. Insgesamt enthält die DIZ-Pressedatenbank ca. 90.000 Dossiers, die untereinander zum "DIZ-Wissensnetz" verlinkt sind. DIZ definiert das Wissensnetz als Alleinstellungsmerkmal und wendet beträchtliche personelle Ressourcen für die Aktualisierung und Qualitätssicherung der Dossiers auf. Im Zuge der Medienkrise mussten sich DIZ der Herausforderung stellen, bei sinkenden Lektoratskapazitäten die Qualität der Informationserschließung im Input zu erhalten. Auf der Outputseite gilt es, eine anspruchsvolle Zielgruppe - u.a. die Redakteure der Süddeutschen Zeitung - passgenau und zeitnah mit den Informationen zu versorgen, die sie für ihre tägliche Arbeit benötigt. Bezogen auf die Ausgangssituation in der Dokumentation der Süddeutschen Zeitung identifizierte DIZ drei Ansatzpunkte, wie die Aufwände auf der Inputseite (Lektorat) zu optimieren sind und gleichzeitig auf der Outputseite (Recherche) das Wissensnetz besser zu vermarkten ist: - (Teil-)Automatische Klassifizierung von Pressetexten (Vorschlagwesen) - Visualisierung des Wissensnetzes - Neue Retrievalmöglichkeiten (Ähnlichkeitssuche, Clustering) Im Bereich "Visualisierung" setzt DIZ auf den Net-Navigator von intelligent views, eine interaktive Visualisierung allgemeiner Graphen, basierend auf einem physikalischen Modell. In den Bereichen automatische Klassifizierung, Ähnlichkeitssuche und Clustering hat DIZ sich für das Produkt nextBot der Firma Brainbot entschieden.

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Subramanian, S.; Shafer, K.E.: Clustering (2001) 0.02

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Date: 5. 5.2003 14:17:22

Reiner, U.: Automatische DDC-Klassifizierung von bibliografischen Titeldatensätzen (2009) 0.01

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Date: 22. 8.2009 12:54:24

HaCohen-Kerner, Y. et al.: Classification using various machine learning methods and combinations of key-phrases and visual features (2016) 0.01

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Date: 1. 2.2016 18:25:22

Schek, M.: Automatische Klassifizierung und Visualisierung im Archiv der Süddeutschen Zeitung (2005) 0.01

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Bock, H.-H.: Datenanalyse zur Strukturierung und Ordnung von Information (1989) 0.01

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Pages: S.1-22

Dubin, D.: Dimensions and discriminability (1998) 0.01

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Date: 22. 9.1997 19:16:05

Automatic classification research at OCLC (2002) 0.01

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Date: 5. 5.2003 9:22:09

Jenkins, C.: Automatic classification of Web resources using Java and Dewey Decimal Classification (1998) 0.01

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Date: 1. 8.1996 22:08:06

Yoon, Y.; Lee, C.; Lee, G.G.: ¬An effective procedure for constructing a hierarchical text classification system (2006) 0.01

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Date: 22. 7.2006 16:24:52

Yi, K.: Automatic text classification using library classification schemes : trends, issues and challenges (2007) 0.01

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Date: 22. 9.2008 18:31:54

Liu, R.-L.: Context recognition for hierarchical text classification (2009) 0.01

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Date: 22. 3.2009 19:11:54

Pfeffer, M.: Automatische Vergabe von RVK-Notationen mittels fallbasiertem Schließen (2009) 0.01

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Date: 22. 8.2009 19:51:28

Zhu, W.Z.; Allen, R.B.: Document clustering using the LSI subspace signature model (2013) 0.01

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Date: 23. 3.2013 13:22:36

Egbert, J.; Biber, D.; Davies, M.: Developing a bottom-up, user-based method of web register classification (2015) 0.01

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Date: 4. 8.2015 19:22:04

Mengle, S.; Goharian, N.: Passage detection using text classification (2009) 0.01

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Date: 22. 3.2009 19:14:43

Liu, R.-L.: ¬A passage extractor for classification of disease aspect information (2013) 0.01

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Date: 28.10.2013 19:22:57

Khoo, C.S.G.; Ng, K.; Ou, S.: ¬An exploratory study of human clustering of Web pages (2003) 0.01

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Date: 12. 9.2004 9:56:22

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