Search (39 results, page 1 of 2)

  • × theme_ss:"Data Mining"
  1. Song, J.; Huang, Y.; Qi, X.; Li, Y.; Li, F.; Fu, K.; Huang, T.: Discovering hierarchical topic evolution in time-stamped documents (2016) 0.03
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  2. Fonseca, F.; Marcinkowski, M.; Davis, C.: Cyber-human systems of thought and understanding (2019) 0.02
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    Date
    7. 3.2019 16:32:22
  3. Advances in knowledge discovery and data mining (1996) 0.02
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    Footnote
    Rez. in: JASIS 49(1998) no.4, S.386-387 (F. Exner)
  4. Peters, G.; Gaese, V.: ¬Das DocCat-System in der Textdokumentation von G+J (2003) 0.01
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    Date
    22. 4.2003 11:45:36
  5. Chowdhury, G.G.: Template mining for information extraction from digital documents (1999) 0.01
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    Date
    2. 4.2000 18:01:22
  6. KDD : techniques and applications (1998) 0.01
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    Footnote
    A special issue of selected papers from the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'97), held Singapore, 22-23 Feb 1997
  7. Budzik, J.; Hammond, K.J.; Birnbaum, L.: Information access in context (2001) 0.01
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  8. Schmid, J.: Data mining : wie finde ich in Datensammlungen entscheidungsrelevante Muster? (1999) 0.01
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  9. Medien-Informationsmanagement : Archivarische, dokumentarische, betriebswirtschaftliche, rechtliche und Berufsbild-Aspekte ; [Frühjahrstagung der Fachgruppe 7 im Jahr 2000 in Weimar und Folgetagung 2001 in Köln] (2003) 0.01
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    Content
    Enthält u.a. die Beiträge (Dokumentarische Aspekte): Günter Perers/Volker Gaese: Das DocCat-System in der Textdokumentation von Gr+J (Weimar 2000) Thomas Gerick: Finden statt suchen. Knowledge Retrieval in Wissensbanken. Mit organisiertem Wissen zu mehr Erfolg (Weimar 2000) Winfried Gödert: Aufbereitung und Rezeption von Information (Weimar 2000) Elisabeth Damen: Klassifikation als Ordnungssystem im elektronischen Pressearchiv (Köln 2001) Clemens Schlenkrich: Aspekte neuer Regelwerksarbeit - Multimediales Datenmodell für ARD und ZDF (Köln 2001) Josef Wandeler: Comprenez-vous only Bahnhof'? - Mehrsprachigkeit in der Mediendokumentation (Köln 200 1)
    Date
    11. 5.2008 19:49:22
  10. Wattenberg, M.; Viégas, F.; Johnson, I.: How to use t-SNE effectively (2016) 0.01
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  11. Data mining, data warehousing and client/server databases : Proceedings of the 8th International Hong Kong Computer Society Database Workshop (Academic Stream) (1997) 0.01
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    Editor
    Fong, J.
  12. Ku, L.-W.; Chen, H.-H.: Mining opinions from the Web : beyond relevance retrieval (2007) 0.01
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    Abstract
    Documents discussing public affairs, common themes, interesting products, and so on, are reported and distributed on the Web. Positive and negative opinions embedded in documents are useful references and feedbacks for governments to improve their services, for companies to market their products, and for customers to purchase their objects. Web opinion mining aims to extract, summarize, and track various aspects of subjective information on the Web. Mining subjective information enables traditional information retrieval (IR) systems to retrieve more data from human viewpoints and provide information with finer granularity. Opinion extraction identifies opinion holders, extracts the relevant opinion sentences, and decides their polarities. Opinion summarization recognizes the major events embedded in documents and summarizes the supportive and the nonsupportive evidence. Opinion tracking captures subjective information from various genres and monitors the developments of opinions from spatial and temporal dimensions. To demonstrate and evaluate the proposed opinion mining algorithms, news and bloggers' articles are adopted. Documents in the evaluation corpora are tagged in different granularities from words, sentences to documents. In the experiments, positive and negative sentiment words and their weights are mined on the basis of Chinese word structures. The f-measure is 73.18% and 63.75% for verbs and nouns, respectively. Utilizing the sentiment words mined together with topical words, we achieve f-measure 62.16% at the sentence level and 74.37% at the document level.
  13. Lam, W.; Yang, C.C.; Menczer, F.: Introduction to the special topic section on mining Web resources for enhancing information retrieval (2007) 0.01
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  14. Kong, S.; Ye, F.; Feng, L.; Zhao, Z.: Towards the prediction problems of bursting hashtags on Twitter (2015) 0.01
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  15. Matson, L.D.; Bonski, D.J.: Do digital libraries need librarians? (1997) 0.01
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    Date
    22.11.1998 18:57:22
  16. Lusti, M.: Data Warehousing and Data Mining : Eine Einführung in entscheidungsunterstützende Systeme (1999) 0.01
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    Date
    17. 7.2002 19:22:06
  17. Amir, A.; Feldman, R.; Kashi, R.: ¬A new and versatile method for association generation (1997) 0.01
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    Source
    Information systems. 22(1997) nos.5/6, S.333-347
  18. Liu, X.; Yu, S.; Janssens, F.; Glänzel, W.; Moreau, Y.; Moor, B.de: Weighted hybrid clustering by combining text mining and bibliometrics on a large-scale journal database (2010) 0.01
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  19. Ebrahimi, M.; ShafieiBavani, E.; Wong, R.; Chen, F.: Twitter user geolocation by filtering of highly mentioned users (2018) 0.01
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  20. Hofstede, A.H.M. ter; Proper, H.A.; Van der Weide, T.P.: Exploiting fact verbalisation in conceptual information modelling (1997) 0.01
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    Source
    Information systems. 22(1997) nos.5/6, S.349-385

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