SWAPit: a multiple views paradigm for exploring associations of texts and structured data

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. Categories and Subject Descriptors H.3.3 [Information Search and Retrieval]: Clustering, Selection process. General Terms Design, Documentation, Human Factors Keywords multiple views, text mining, document maps, ontologies, relational data, visual interaction.

• Type: Conference
• Year: 2004
• Where: AVI
• Authors: Andreas Becks, Christian Seeling
• Keywords: AVI 2004, Relational Data, Relational Data Sources, Software Engineering, Structured Data