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Chowdhury, G.G.: Template mining for information extraction from digital documents (1999)
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- Date
- 2. 4.2000 18:01:22
- Language
- e
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Budzik, J.; Hammond, K.J.; Birnbaum, L.: Information access in context (2001)
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- e
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Matson, L.D.; Bonski, D.J.: Do digital libraries need librarians? (1997)
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- Date
- 22.11.1998 18:57:22
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Amir, A.; Feldman, R.; Kashi, R.: ¬A new and versatile method for association generation (1997)
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- Information systems. 22(1997) nos.5/6, S.333-347
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Hofstede, A.H.M. ter; Proper, H.A.; Van der Weide, T.P.: Exploiting fact verbalisation in conceptual information modelling (1997)
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- Information systems. 22(1997) nos.5/6, S.349-385
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Li, J.; Zhang, P.; Cao, J.: External concept support for group support systems through Web mining (2009)
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Peters, G.; Gaese, V.: ¬Das DocCat-System in der Textdokumentation von G+J (2003)
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- Date
- 22. 4.2003 11:45:36
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Huvila, I.: Mining qualitative data on human information behaviour from the Web (2010)
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- Information und Wissen: global, sozial und frei? Proceedings des 12. Internationalen Symposiums für Informationswissenschaft (ISI 2011) ; Hildesheim, 9. - 11. März 2011. Hrsg.: J. Griesbaum, T. Mandl u. C. Womser-Hacker
-
Hereth, J.; Stumme, G.; Wille, R.; Wille, U.: Conceptual knowledge discovery and data analysis (2000)
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- Abstract
- In this paper, we discuss Conceptual Knowledge Discovery in Databases (CKDD) in its connection with Data Analysis. Our approach is based on Formal Concept Analysis, a mathematical theory which has been developed and proven useful during the last 20 years. Formal Concept Analysis has led to a theory of conceptual information systems which has been applied by using the management system TOSCANA in a wide range of domains. In this paper, we use such an application in database marketing to demonstrate how methods and procedures of CKDD can be applied in Data Analysis. In particular, we show the interplay and integration of data mining and data analysis techniques based on Formal Concept Analysis. The main concern of this paper is to explain how the transition from data to knowledge can be supported by a TOSCANA system. To clarify the transition steps we discuss their correspondence to the five levels of knowledge representation established by R. Brachman and to the steps of empirically grounded theory building proposed by A. Strauss and J. Corbin
- Language
- e
-
Li, D.; Tang, J.; Ding, Y.; Shuai, X.; Chambers, T.; Sun, G.; Luo, Z.; Zhang, J.: Topic-level opinion influence model (TOIM) : an investigation using tencent microblogging (2015)
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Pons-Porrata, A.; Berlanga-Llavori, R.; Ruiz-Shulcloper, J.: Topic discovery based on text mining techniques (2007)
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Sánchez, D.; Chamorro-Martínez, J.; Vila, M.A.: Modelling subjectivity in visual perception of orientation for image retrieval (2003)
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Song, J.; Huang, Y.; Qi, X.; Li, Y.; Li, F.; Fu, K.; Huang, T.: Discovering hierarchical topic evolution in time-stamped documents (2016)
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Hallonsten, O.; Holmberg, D.: Analyzing structural stratification in the Swedish higher education system : data contextualization with policy-history analysis (2013)
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- Date
- 22. 3.2013 19:43:01
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Vaughan, L.; Chen, Y.: Data mining from web search queries : a comparison of Google trends and Baidu index (2015)
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- Journal of the Association for Information Science and Technology. 66(2015) no.1, S.13-22
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Fonseca, F.; Marcinkowski, M.; Davis, C.: Cyber-human systems of thought and understanding (2019)
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- Date
- 7. 3.2019 16:32:22
- Language
- e
-
Schmid, J.: Data mining : wie finde ich in Datensammlungen entscheidungsrelevante Muster? (1999)
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Gill, A.J.; Hinrichs-Krapels, S.; Blanke, T.; Grant, J.; Hedges, M.; Tanner, S.: Insight workflow : systematically combining human and computational methods to explore textual data (2017)
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- Language
- e
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Jäger, L.: Von Big Data zu Big Brother (2018)
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- Abstract
- 1983 bewegte ein einziges Thema die gesamte Bundesrepublik: die geplante Volkszählung. Jeder Haushalt in Westdeutschland sollte Fragebögen mit 36 Fragen zur Wohnsituation, den im Haushalt lebenden Personen und über ihre Einkommensverhältnisse ausfüllen. Es regte sich massiver Widerstand, hunderte Bürgerinitiativen formierten sich im ganzen Land gegen die Befragung. Man wollte nicht "erfasst" werden, die Privatsphäre war heilig. Es bestand die (berechtigte) Sorge, dass die Antworten auf den eigentlich anonymisierten Fragebögen Rückschlüsse auf die Identität der Befragten zulassen. Das Bundesverfassungsgericht gab den Klägern gegen den Zensus Recht: Die geplante Volkszählung verstieß gegen den Datenschutz und damit auch gegen das Grundgesetz. Sie wurde gestoppt. Nur eine Generation später geben wir sorglos jedes Mal beim Einkaufen die Bonuskarte der Supermarktkette heraus, um ein paar Punkte für ein Geschenk oder Rabatte beim nächsten Einkauf zu sammeln. Und dabei wissen wir sehr wohl, dass der Supermarkt damit unser Konsumverhalten bis ins letzte Detail erfährt. Was wir nicht wissen, ist, wer noch Zugang zu diesen Daten erhält. Deren Käufer bekommen nicht nur Zugriff auf unsere Einkäufe, sondern können über sie auch unsere Gewohnheiten, persönlichen Vorlieben und Einkommen ermitteln. Genauso unbeschwert surfen wir im Internet, googeln und shoppen, mailen und chatten. Google, Facebook und Microsoft schauen bei all dem nicht nur zu, sondern speichern auf alle Zeiten alles, was wir von uns geben, was wir einkaufen, was wir suchen, und verwenden es für ihre eigenen Zwecke. Sie durchstöbern unsere E-Mails, kennen unser persönliches Zeitmanagement, verfolgen unseren momentanen Standort, wissen um unsere politischen, religiösen und sexuellen Präferenzen (wer kennt ihn nicht, den Button "an Männern interessiert" oder "an Frauen interessiert"?), unsere engsten Freunde, mit denen wir online verbunden sind, unseren Beziehungsstatus, welche Schule wir besuchen oder besucht haben und vieles mehr.
- Date
- 22. 1.2018 11:33:49
-
Hölzig, C.: Google spürt Grippewellen auf : Die neue Anwendung ist bisher auf die USA beschränkt (2008)
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- Date
- 3. 5.1997 8:44:22
