-
Ohly, H.P.: Bibliometric mining : added value from document analysis and retrieval (2008)
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- Language
- e
- Source
- Kompatibilität, Medien und Ethik in der Wissensorganisation - Compatibility, Media and Ethics in Knowledge Organization: Proceedings der 10. Tagung der Deutschen Sektion der Internationalen Gesellschaft für Wissensorganisation Wien, 3.-5. Juli 2006 - Proceedings of the 10th Conference of the German Section of the International Society of Knowledge Organization Vienna, 3-5 July 2006. Ed.: H.P. Ohly, S. Netscher u. K. Mitgutsch
-
Schwartz, D.: Graphische Datenanalyse für digitale Bibliotheken : Leistungs- und Funktionsumfang moderner Analyse- und Visualisierungsinstrumente (2006)
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- Source
- Vom Wandel der Wissensorganisation im Informationszeitalter: Festschrift für Walther Umstätter zum 65. Geburtstag, hrsg. von P. Hauke u. K. Umlauf
-
Data mining, data warehousing and client/server databases : Proceedings of the 8th International Hong Kong Computer Society Database Workshop (Industrial Stream) (1997)
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- Editor
- Siu, B., P.K.M. Kwan u. B. Lam
- Language
- e
-
Amir, A.; Feldman, R.; Kashi, R.: ¬A new and versatile method for association generation (1997)
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- Date
- 5. 4.1996 15:29:15
- Language
- e
- Source
- Information systems. 22(1997) nos.5/6, S.333-347
-
Ma, Z.; Sun, A.; Cong, G.: On predicting the popularity of newly emerging hashtags in Twitter (2013)
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- Abstract
- Because of Twitter's popularity and the viral nature of information dissemination on Twitter, predicting which Twitter topics will become popular in the near future becomes a task of considerable economic importance. Many Twitter topics are annotated by hashtags. In this article, we propose methods to predict the popularity of new hashtags on Twitter by formulating the problem as a classification task. We use five standard classification models (i.e., Naïve bayes, k-nearest neighbors, decision trees, support vector machines, and logistic regression) for prediction. The main challenge is the identification of effective features for describing new hashtags. We extract 7 content features from a hashtag string and the collection of tweets containing the hashtag and 11 contextual features from the social graph formed by users who have adopted the hashtag. We conducted experiments on a Twitter data set consisting of 31 million tweets from 2 million Singapore-based users. The experimental results show that the standard classifiers using the extracted features significantly outperform the baseline methods that do not use these features. Among the five classifiers, the logistic regression model performs the best in terms of the Micro-F1 measure. We also observe that contextual features are more effective than content features.
- Date
- 25. 6.2013 19:05:29
- Language
- e
-
Heyer, G.; Läuter, M.; Quasthoff, U.; Wolff, C.: Texttechnologische Anwendungen am Beispiel Text Mining (2000)
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- Source
- Sprachtechnologie für eine dynamische Wirtschaft im Medienzeitalter - Language technologies for dynamic business in the age of the media - L'ingénierie linguistique au service de la dynamisation économique à l'ère du multimédia: Tagungsakten der XXVI. Jahrestagung der Internationalen Vereinigung Sprache und Wirtschaft e.V., 23.-25.11.2000, Fachhochschule Köln. Hrsg.: K.-D. Schmitz
-
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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- Date
- 5. 4.1996 15:29:15
- Language
- e
- Source
- Information systems. 22(1997) nos.5/6, S.349-385
-
Fayyad, U.; Piatetsky-Shapiro, G.; Smyth, P.: From data mining to knowledge discovery in databases (1996)
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- Language
- e
-
Raan, A.F.J. van; Noyons, E.C.M.: Discovery of patterns of scientific and technological development and knowledge transfer (2002)
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- Language
- e
- Source
- Gaining insight from research information (CRIS2002): Proceedings of the 6th International Conference an Current Research Information Systems, University of Kassel, August 29 - 31, 2002. Eds: W. Adamczak u. A. Nase
-
Tiefschürfen in Datenbanken (2002)
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- Content
- Enthält die Beiträge: Kruse, R., C. Borgelt: Suche im Datendschungel - Borgelt, C. u. R. Kruse: Unsicheres Wissen nutzen - Wrobel, S.: Lern- und Entdeckungsverfahren - Keim, D.A.: Data Mining mit bloßem Auge
- Date
- 31.12.1996 19:29:41
-
Chardonnens, A.; Hengchen, S.: Text mining for cultural heritage institutions : a 5-step method for cultural heritage institutions (2017)
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- Language
- e
- Source
- Everything changes, everything stays the same? - Understanding information spaces : Proceedings of the 15th International Symposium of Information Science (ISI 2017), Berlin/Germany, 13th - 15th March 2017. Eds.: M. Gäde, V. Trkulja u. V. Petras
-
Dang, X.H.; Ong. K.-L.: Knowledge discovery in data streams (2009)
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- Footnote
- Vgl.: http://www.tandfonline.com/doi/book/10.1081/E-ELIS3.
- Language
- e
-
Huvila, I.: Mining qualitative data on human information behaviour from the Web (2010)
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- Language
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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
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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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Budzik, J.; Hammond, K.J.; Birnbaum, L.: Information access in context (2001)
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Kantardzic, M.: Data mining : concepts, models, methods, and algorithms (2003)
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Chowdhury, G.G.: Template mining for information extraction from digital documents (1999)
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Liu, B.: Web data mining : exploring hyperlinks, contents, and usage data (2011)
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Relational data mining (2001)
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Kulathuramaiyer, N.; Maurer, H.: Implications of emerging data mining (2009)
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- Social Semantic Web: Web 2.0, was nun? Hrsg.: A. Blumauer u. T. Pellegrini
