An exploratory evaluation of three interfaces for browsing large hierarchical tables of contents
ACM Transactions on Information Systems (TOIS)
Guidelines for using multiple views in information visualization
AVI '00 Proceedings of the working conference on Advanced visual interfaces
AVI '00 Proceedings of the working conference on Advanced visual interfaces
A modular approach for exploring the semantic structure of technical document collections
AVI '00 Proceedings of the working conference on Advanced visual interfaces
Document Warehousing and Text Mining: Techniques for Improving Business Operations, Marketing, and Sales
Visualizing the Semantic Web: Xml-Based Internet and Information Visualization
Visualizing the Semantic Web: Xml-Based Internet and Information Visualization
Multi-Faceted Insight Through Interoperable Visual Information Analysis Paradigms
INFOVIS '98 Proceedings of the 1998 IEEE Symposium on Information Visualization
The Eyes Have It: A Task by Data Type Taxonomy for Information Visualizations
VL '96 Proceedings of the 1996 IEEE Symposium on Visual Languages
Exploiting Metadata for Ontology-Based Visual Exploration of Weakly Structured Text Documents
IV '03 Proceedings of the Seventh International Conference on Information Visualization
The neighborhood viewer: a paradigm for exploring image databases
CHI EA '97 CHI '97 Extended Abstracts on Human Factors in Computing Systems
Collaborative knowledge visualization for cross-community learning
Knowledge and Information Visualization
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Visualization interfaces that offer multiple coordinated views on a particular set of data items are useful for navigating and exploring complex information spaces. In this paper we address the problem of mining text information which is associated with structured data from relational data sources. We present a multi-view paradigm that closely integrates the analysis of unstructured text data with related structured data sets. Our concept brings together views on text similarity, text categories, and associated relational attributes for application fields like customer relationship management or business intelligence. A prototype is presented that exemplarily implements our multi-view framework.