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Information visualization in data mining and knowledge discovery (2002)
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- Date
- 23. 3.2008 19:10:22
- Footnote
- Rez. in: JASIST 54(2003) no.9, S.905-906 (C.A. Badurek): "Visual approaches for knowledge discovery in very large databases are a prime research need for information scientists focused an extracting meaningful information from the ever growing stores of data from a variety of domains, including business, the geosciences, and satellite and medical imagery. This work presents a summary of research efforts in the fields of data mining, knowledge discovery, and data visualization with the goal of aiding the integration of research approaches and techniques from these major fields. The editors, leading computer scientists from academia and industry, present a collection of 32 papers from contributors who are incorporating visualization and data mining techniques through academic research as well application development in industry and government agencies. Information Visualization focuses upon techniques to enhance the natural abilities of humans to visually understand data, in particular, large-scale data sets. It is primarily concerned with developing interactive graphical representations to enable users to more intuitively make sense of multidimensional data as part of the data exploration process. It includes research from computer science, psychology, human-computer interaction, statistics, and information science. Knowledge Discovery in Databases (KDD) most often refers to the process of mining databases for previously unknown patterns and trends in data. Data mining refers to the particular computational methods or algorithms used in this process. The data mining research field is most related to computational advances in database theory, artificial intelligence and machine learning. This work compiles research summaries from these main research areas in order to provide "a reference work containing the collection of thoughts and ideas of noted researchers from the fields of data mining and data visualization" (p. 8). It addresses these areas in three main sections: the first an data visualization, the second an KDD and model visualization, and the last an using visualization in the knowledge discovery process. The seven chapters of Part One focus upon methodologies and successful techniques from the field of Data Visualization. Hoffman and Grinstein (Chapter 2) give a particularly good overview of the field of data visualization and its potential application to data mining. An introduction to the terminology of data visualization, relation to perceptual and cognitive science, and discussion of the major visualization display techniques are presented. Discussion and illustration explain the usefulness and proper context of such data visualization techniques as scatter plots, 2D and 3D isosurfaces, glyphs, parallel coordinates, and radial coordinate visualizations. Remaining chapters present the need for standardization of visualization methods, discussion of user requirements in the development of tools, and examples of using information visualization in addressing research problems.
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Intelligent information processing and web mining : Proceedings of the International IIS: IIPWM'03 Conference held in Zakopane, Poland, June 2-5, 2003 (2003)
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Budzik, J.; Hammond, K.J.; Birnbaum, L.: Information access in context (2001)
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- Knowledge-based systems. 14(2001) nos.1/2, S.37-53
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Fong, A.C.M.: Mining a Web citation database for document clustering (2002)
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- Applied artificial intelligence. 16(2002) no.4, S.283-292
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Chen, S.Y.; Liu, X.: ¬The contribution of data mining to information science : making sense of it all (2005)
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- Journal of information science. 30(2005) no.6, S.550-
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Relational data mining (2001)
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- Editor
- Dzeroski, S. u. N. Lavrac
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- XIX,398 S
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Knowledge management in fuzzy databases (2000)
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Ohly, H.P.: Bibliometric mining : added value from document analysis and retrieval (2008)
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- S.181-186
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- 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
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Loh, S.; Oliveira, J.P.M. de; Gastal, F.L.: Knowledge discovery in textual documentation : qualitative and quantitative analyses (2001)
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- Journal of documentation. 57(2001) no.5, S.577-590
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Perugini, S.; Ramakrishnan, N.: Mining Web functional dependencies for flexible information access (2007)
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- Journal of the American Society for Information Science and Technology. 58(2007) no.12, S.1805-1819
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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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Bath, P.A.: Data mining in health and medical information (2003)
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- Annual review of information science and technology. 38(2004), S.331-370
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Nicholson, S.: Bibliomining for automated collection development in a digital library setting : using data mining to discover Web-based scholarly research works (2003)
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- Journal of the American Society for Information Science and technology. 54(2003) no.12, S.1081-1090
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Classification, automation, and new media : Proceedings of the 24th Annual Conference of the Gesellschaft für Klassifikation e.V., University of Passau, March 15 - 17, 2000 (2002)
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Survey of text mining : clustering, classification, and retrieval (2004)
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Liu, Y.; Zhang, M.; Cen, R.; Ru, L.; Ma, S.: Data cleansing for Web information retrieval using query independent features (2007)
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Lam, W.; Yang, C.C.; Menczer, F.: Introduction to the special topic section on mining Web resources for enhancing information retrieval (2007)
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Baeza-Yates, R.; Hurtado, C.; Mendoza, M.: Improving search engines by query clustering (2007)
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Zhou, L.; Chaovalit, P.: Ontology-supported polarity mining (2008)
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Liu, W.; Weichselbraun, A.; Scharl, A.; Chang, E.: Semi-automatic ontology extension using spreading activation (2005)
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- Journal of universal knowledge management. 0(2005) no.1, S.50-58
