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  1. Chen, Y.-S.; Chong, P.P.: Information productivity modeling : the Simon-Yule approach (1998) 0.14 
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  2. Ackermann, E.: Piaget's constructivism, Papert's constructionism : what's the difference? (2001) 0.11 
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    Content
    Vgl.: https://www.semanticscholar.org/paper/Piaget-%E2%80%99-s-Constructivism-%2C-Papert-%E2%80%99-s-%3A-What-%E2%80%99-s-Ackermann/89cbcc1e740a4591443ff4765a6ae8df0fdf5554. Darunter weitere Hinweise auf verwandte Beiträge. Auch unter: Learning Group Publication 5(2001) no.3, S.438.
  3. Chakrabarti, P.P.: Algorithms for searching explicit AND/OR graphs and their applications to problem reduction search (1994) 0.08 
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  4. Chen, Y.-S.; Chong, P.P.; Tong, M.Y.: Dynamic behavior of Bradford's law (1995) 0.08 
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  5. Devadason, F.J.; Lingam, P.P.: ¬A methodology for the identification of information needs of users (1997) 0.08 
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  6. Clark, D.A.; Mitra, P.P.; Wang, S.S.-H.: ¬The mammalian brain : a question of scale (2001) 0.07 
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  7. Burnett, P.P.: Emerging from the bibliographic wilderness : Catalogue automation in the Bodleian Library, University of Oxford (2000) 0.07 
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  8. Ray, P.P.: Influence of Manu on Ranganthan's philosophy of library science : an overview (2015) 0.07 
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  9. 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
  10. From information to knowledge : conceptual and content analysis by computer (1995) 0.05 
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    Content
    SCHMIDT, K.M.: Concepts - content - meaning: an introduction; DUCHASTEL, J. et al.: The SACAO project: using computation toward textual data analysis; PAQUIN, L.-C. u. L. DUPUY: An approach to expertise transfer: computer-assisted text analysis; HOGENRAAD, R., Y. BESTGEN u. J.-L. NYSTEN: Terrorist rhetoric: texture and architecture; MOHLER, P.P.: On the interaction between reading and computing: an interpretative approach to content analysis; LANCASHIRE, I.: Computer tools for cognitive stylistics; MERGENTHALER, E.: An outline of knowledge based text analysis; NAMENWIRTH, J.Z.: Ideography in computer-aided content analysis; WEBER, R.P. u. J.Z. Namenwirth: Content-analytic indicators: a self-critique; McKINNON, A.: Optimizing the aberrant frequency word technique; ROSATI, R.: Factor analysis in classical archaeology: export patterns of Attic pottery trade; PETRILLO, P.S.: Old and new worlds: ancient coinage and modern technology; DARANYI, S., S. MARJAI u.a.: Caryatids and the measurement of semiosis in architecture; ZARRI, G.P.: Intelligent information retrieval: an application in the field of historical biographical data; BOUCHARD, G., R. ROY u.a.: Computers and genealogy: from family reconstitution to population reconstruction; DEMÉLAS-BOHY, M.-D. u. M. RENAUD: Instability, networks and political parties: a political history expert system prototype; DARANYI, S., A. ABRANYI u. G. KOVACS: Knowledge extraction from ethnopoetic texts by multivariate statistical methods; FRAUTSCHI, R.L.: Measures of narrative voice in French prose fiction applied to textual samples from the enlightenment to the twentieth century; DANNENBERG, R. u.a.: A project in computer music: the musician's workbench
  11. Favato Barcelos, P.P.; Sales, T.P.; Fumagalli, M.; Guizzardi, G.; Valle Sousa, I.; Fonseca, C.M.; Romanenko, E.; Kritz, J.: ¬A FAIR model catalog for ontology-driven conceptual modeling research (2022) 0.05 
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  12. Kleineberg, M.: Context analysis and context indexing : formal pragmatics in knowledge organization (2014) 0.04 
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    Source
    http://www.google.de/url?sa=t&rct=j&q=&esrc=s&source=web&cd=5&ved=0CDQQFjAE&url=http%3A%2F%2Fdigbib.ubka.uni-karlsruhe.de%2Fvolltexte%2Fdocuments%2F3131107&ei=HzFWVYvGMsiNsgGTyoFI&usg=AFQjCNE2FHUeR9oQTQlNC4TPedv4Mo3DaQ&sig2=Rlzpr7a3BLZZkqZCXXN_IA&bvm=bv.93564037,d.bGg&cad=rja
  13. Billal, B.; Fonseca, A.; Sadat, F.; Lounis, H.: Semi-supervised learning and social media text analysis towards multi-labeling categorization (2017) 0.04 
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    Abstract
    In traditional text classification, classes are mutually exclusive, i.e. it is not possible to have one text or text fragment classified into more than one class. On the other hand, in multi-label classification an individual text may belong to several classes simultaneously. This type of classification is required by a large number of current applications such as big data classification, images and video annotation. Supervised learning is the most used type of machine learning in the classification task. It requires large quantities of labeled data and the intervention of a human tagger in the creation of the training sets. When the data sets become very large or heavily noisy, this operation can be tedious, prone to error and time consuming. In this case, semi-supervised learning, which requires only few labels, is a better choice. In this paper, we study and evaluate several methods to address the problem of multi-label classification using semi-supervised learning and data from social networks. First, we propose a linguistic pre-processing involving tokeni-sation, recognition of named entities and hashtag segmentation in order to decrease the noise in this type of massive and unstructured real data and then we perform a word sense disambiguation using WordNet. Second, several experiments related to multi-label classification and semi-supervised learning are carried out on these data sets and compared to each other. These evaluations compare the results of the approaches considered. This paper proposes a method for combining semi-supervised methods with a graph method for the extraction of subjects in social networks using a multi-label classification approach. Experiments show that the performance of the proposed model increases in 4 p.p. the precision of the classification when compared to a baseline.
  14. Popper, K.R.: Three worlds : the Tanner lecture on human values. Deliverd at the University of Michigan, April 7, 1978 (1978) 0.03 
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    https%3A%2F%2Ftannerlectures.utah.edu%2F_documents%2Fa-to-z%2Fp%2Fpopper80.pdf&usg=AOvVaw3f4QRTEH-OEBmoYr2J_c7H
  15. Jascó, P.: Searching for images by similarity online (1998) 0.03 
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    Date
    29.11.2004 13:03:22
    Source
    Online. 22(1998) no.6, S.99-102
  16. Hawking, D.; Robertson, S.: On collection size and retrieval effectiveness (2003) 0.03 
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    Date
    14. 8.2005 14:22:22
  17. Buzydlowski, J.W.; White, H.D.; Lin, X.: Term Co-occurrence Analysis as an Interface for Digital Libraries (2002) 0.03 
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    Date
    22. 2.2003 17:25:39
    22. 2.2003 18:16:22
  18. Vetere, G.; Lenzerini, M.: Models for semantic interoperability in service-oriented architectures (2005) 0.03 
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    Content
    Vgl.: http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=5386707&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D5386707.
  19. Dahlberg, I.: Conceptual definitions for INTERCONCEPT (1981) 0.03 
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    Source
    International classification. 8(1981), S.16-22
  20. Pietris, M.K.D.: LCSH update (1988) 0.03 
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                2.0 = termFreq=2.0
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    Source
    Cataloguing Australia. 13(1988), S.19-22

Authors

Years

Types

  • a 1937
  • m 151
  • s 98
  • el 70
  • b 31
  • r 10
  • x 8
  • i 3
  • n 2
  • p 2
  • h 1
  • More… Less…

Themes

Subjects

Classifications