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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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Peters, G.; Gaese, V.: ¬Das DocCat-System in der Textdokumentation von G+J (2003)
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- 2003
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Brückner, T.; Dambeck, H.: Sortierautomaten : Grundlagen der Textklassifizierung (2003)
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- c't. 2003, H.19, S.192-197
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- 2003
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Medien-Informationsmanagement : Archivarische, dokumentarische, betriebswirtschaftliche, rechtliche und Berufsbild-Aspekte ; [Frühjahrstagung der Fachgruppe 7 im Jahr 2000 in Weimar und Folgetagung 2001 in Köln] (2003)
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- 2003
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Bath, P.A.: Data mining in health and medical information (2003)
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Fenstermacher, K.D.; Ginsburg, M.: Client-side monitoring for Web mining (2003)
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- Journal of the American Society for Information Science and technology. 54(2003) no.7, S.625-637
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- 2003
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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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- Information processing and management. 39(2003) no.2, S.251-266
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- 2003
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Chowdhury, G.G.: Template mining for information extraction from digital documents (1999)
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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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- 2003
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Haravu, L.J.; Neelameghan, A.: Text mining and data mining in knowledge organization and discovery : the making of knowledge-based products (2003)
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- Cataloging and classification quarterly. 37(2003) nos.1/2, S.96-114
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- 2003
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KDD : techniques and applications (1998)
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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
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Kantardzic, M.: Data mining : concepts, models, methods, and algorithms (2003)
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- QA76.9.D343K36 2003
- LCC
- QA76.9.D343K36 2003
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- 2003
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Chen, H.; Chau, M.: Web mining : machine learning for Web applications (2003)
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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.
-
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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Lusti, M.: Data Warehousing and Data Mining : Eine Einführung in entscheidungsunterstützende Systeme (1999)
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- 17. 7.2002 19:22:06
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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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Chakrabarti, S.: Mining the Web : discovering knowledge from hypertext data (2003)
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- Year
- 2003
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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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Lackes, R.; Tillmanns, C.: Data Mining für die Unternehmenspraxis : Entscheidungshilfen und Fallstudien mit führenden Softwarelösungen (2006)
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- Date
- 22. 3.2008 14:46:06
