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Trunk, D.: Semantische Netze in Informationssystemen : Verbesserung der Suche durch Interaktion und Visualisierung (2005)
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- Abstract
- Semantische Netze unterstützen den Suchvorgang im Information Retrieval. Sie bestehen aus relationierten Begriffen und helfen dem Nutzer das richtige Vokabular zur Fragebildung zu finden. Eine leicht und intuitiv erfassbare Darstellung und eine interaktive Bedienungsmöglichkeit optimieren den Suchprozess mit der Begriffsstruktur. Als Interaktionsform bietet sich Hy-pertext mit dem etablierte Point- und Klickverfahren an. Eine Visualisierung zur Unterstützung kognitiver Fähigkeiten kann durch eine Darstellung der Informationen mit Hilfe von Punkten und Linien erfolgen. Vorgestellt wer-den die Anwendungsbeispiele Wissensnetz im Brockhaus multimedial, WordSurfer der Firma BiblioMondo, SpiderSearch der Firma BOND und Topic Maps Visualization in dandelon.com und im Portal Informationswis-senschaft der Firma AGI - Information Management Consultants.
- Date
- 30. 1.2007 18:22:41
- Object
- Brockhaus multimedial
-
Trunk, D.: Inhaltliche Semantische Netze in Informationssystemen : Verbesserung der Suche durch Interaktion und Visualisierung (2005)
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- Abstract
- Semantische Netze unterstützen den Suchvorgang im Information Retrieval. Sie bestehen aus relationierten Begriffen und helfen dem Nutzer, das richtige Vokabular zur Fragebildung zu finden. Eine leicht und intuitiv erfassbare Darstellung und eine interaktive Bedienungsmöglichkeit optimieren den Suchprozess mit der Begriffsstruktur. Als Interaktionsform bietet sich Hypertext mit seinem Point- und Klickverfahren an. Die Visualisierung erfolgt als Netzstruktur aus Punkten und Linien. Es werden die Anwendungsbeispiele Wissensnetz im Brockhaus multimedial, WordSurfer der Firma BiblioMondo, SpiderSearch der Firma BOND und Topic Maps Visualization in dandelon.com und im Portal Informationswissenschaft der Firma AGI - Information Management Consultants vorgestellt.
- Object
- Brockhaus multimedial
-
IEEE symposium on information visualization 2003 : Seattle, Washington, October 19 - 21, 2003 ; InfoVis 2003. Proceedings (2003)
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- Classification
- TK7882.I6I24 2003
SS 2003
- LCC
- TK7882.I6I24 2003
- RSWK
- Computergraphik / Visualisierung / Kongress / Seattle <Wash., 2003>
- RVK
- SS 2003
- Subject
- Computergraphik / Visualisierung / Kongress / Seattle <Wash., 2003>
- Year
- 2003
-
Thissen, F.: Screen-Design-Manual : Communicating Effectively Through Multimedia (2003)
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- Date
- 22. 3.2008 14:29:25
- Year
- 2003
-
Chen, C.: CiteSpace II : detecting and visualizing emerging trends and transient patterns in scientific literature (2006)
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- Abstract
- This article describes the latest development of a generic approach to detecting and visualizing emerging trends and transient patterns in scientific literature. The work makes substantial theoretical and methodological contributions to progressive knowledge domain visualization. A specialty is conceptualized and visualized as a time-variant duality between two fundamental concepts in information science: research fronts and intellectual bases. A research front is defined as an emergent and transient grouping of concepts and underlying research issues. The intellectual base of a research front is its citation and co-citation footprint in scientific literature - an evolving network of scientific publications cited by research-front concepts. Kleinberg's (2002) burst-detection algorithm is adapted to identify emergent research-front concepts. Freeman's (1979) betweenness centrality metric is used to highlight potential pivotal points of paradigm shift over time. Two complementary visualization views are designed and implemented: cluster views and time-zone views. The contributions of the approach are that (a) the nature of an intellectual base is algorithmically and temporally identified by emergent research-front terms, (b) the value of a co-citation cluster is explicitly interpreted in terms of research-front concepts, and (c) visually prominent and algorithmically detected pivotal points substantially reduce the complexity of a visualized network. The modeling and visualization process is implemented in CiteSpace II, a Java application, and applied to the analysis of two research fields: mass extinction (1981-2004) and terrorism (1990-2003). Prominent trends and pivotal points in visualized networks were verified in collaboration with domain experts, who are the authors of pivotal-point articles. Practical implications of the work are discussed. A number of challenges and opportunities for future studies are identified.
- Date
- 22. 7.2006 16:11:05
-
Sidhom, S.; Hassoun, M.: Morpho-syntactic parsing to text mining environment : NP recognition model to knowledge visualization and information (2003)
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- Year
- 2003
-
Leide, J.E.; Large, A.; Beheshti, J.; Brooks, M.; Cole, C.: Visualization schemes for domain novices exploring a topic space : the navigation classification scheme (2003)
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- Source
- Information processing and management. 39(2003) no.6, S.923-940
- Year
- 2003
-
Eibl, M.: Visualisierung im Document Retrieval : Theoretische und praktische Zusammenführung von Softwareergonomie und Graphik Design (2003)
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- 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.
-
Haller, S.H.M.: Mappingverfahren zur Wissensorganisation (2002)
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- Date
- 30. 5.2010 16:22:35
-
Platis, N. et al.: Visualization of uncertainty in tag clouds (2016)
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- Date
- 1. 2.2016 18:25:22
-
Börner, K.: Atlas of knowledge : anyone can map (2015)
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- Date
- 22. 1.2017 16:54:03
22. 1.2017 17:10:56
-
Beagle, D.: Visualizing keyword distribution across multidisciplinary c-space (2003)
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- Source
- D-Lib magazine. 9(2003) no.6, x S
- Year
- 2003
-
Palm, F.: QVIZ : Query and context based visualization of time-spatial cultural dynamics (2007)
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- Content
- Vortrag anlässlich des Workshops: "Extending the multilingual capacity of The European Library in the EDL project Stockholm, Swedish National Library, 22-23 November 2007".
-
Thissen, F.: Screen-Design-Handbuch : Effektiv informieren und kommunizieren mit Multimedia (2001)
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- Date
- 22. 3.2008 14:35:21
-
Osinska, V.; Bala, P.: New methods for visualization and improvement of classification schemes : the case of computer science (2010)
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- 22. 7.2010 19:36:46
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Jäger-Dengler-Harles, I.: Informationsvisualisierung und Retrieval im Fokus der Infromationspraxis (2013)
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- Date
- 4. 2.2015 9:22:39
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Börner, K.; Chen, C.; Boyack, K.W.: Visualizing knowledge domains (2002)
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- Source
- Annual review of information science and technology. 37(2003), S.179-258
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Wu, K.-C.; Hsieh, T.-Y.: Affective choosing of clustering and categorization representations in e-book interfaces (2016)
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Wu, I.-C.; Vakkari, P.: Effects of subject-oriented visualization tools on search by novices and intermediates (2018)
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