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Chowdhury, G.G.: Template mining for information extraction from digital documents (1999)
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- 2. 4.2000 18:01:22
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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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Matson, L.D.; Bonski, D.J.: Do digital libraries need librarians? (1997)
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- Date
- 22.11.1998 18:57:22
-
Amir, A.; Feldman, R.; Kashi, R.: ¬A new and versatile method for association generation (1997)
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- Source
- 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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- Source
- Information systems. 22(1997) nos.5/6, S.349-385
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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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- Source
- 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
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Howlett, D.: Digging deep for treasure (1998)
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-
Carter, D.; Sholler, D.: Data science on the ground : hype, criticism, and everyday work (2016)
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-
Derek Doran, D.; Gokhale, S.S.: ¬A classification framework for web robots (2012)
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Miao, Q.; Li, Q.; Zeng, D.: Fine-grained opinion mining by integrating multiple review sources (2010)
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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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-
Thelwall, M.; Wilkinson, D.; Uppal, S.: Data mining emotion in social network communication : gender differences in MySpace (2009)
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Thelwall, M.; Wilkinson, D.: Public dialogs in social network sites : What is their purpose? (2010)
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-
Mohr, J.W.; Bogdanov, P.: Topic models : what they are and why they matter (2013)
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- Abstract
- We provide a brief, non-technical introduction to the text mining methodology known as "topic modeling." We summarize the theory and background of the method and discuss what kinds of things are found by topic models. Using a text corpus comprised of the eight articles from the special issue of Poetics on the subject of topic models, we run a topic model on these articles, both as a way to introduce the methodology and also to help summarize some of the ways in which social and cultural scientists are using topic models. We review some of the critiques and debates over the use of the method and finally, we link these developments back to some of the original innovations in the field of content analysis that were pioneered by Harold D. Lasswell and colleagues during and just after World War II.
-
Zhang, Z.; Li, Q.; Zeng, D.; Ga, H.: Extracting evolutionary communities in community question answering (2014)
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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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-
Cohen, D.J.: From Babel to knowledge : data mining large digital collections (2006)
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- Source
- D-Lib magazine. 12(2006) no.3, x S
