Human issues in the use of pattern recognition techniques
Neural networks and pattern recognition in human-computer interaction
CHI '94 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
HIBROWSE for bibliographic database
Journal of Information Science
Scatter/gather browsing communicates the topic structure of a very large text collection
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Polyarchy visualization: visualizing multiple intersecting hierarchies
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Machine Learning
PESTO: An Integrated Query/Browser for Object Databases
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Multiple Foci Drill-Down through Tuple and Attribute Aggregation Polyarchies in Tabular Data
INFOVIS '02 Proceedings of the IEEE Symposium on Information Visualization (InfoVis'02)
VLDB '05 Proceedings of the 31st international conference on Very large data bases
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Traditional database query formulation is intensional: at the level of schemas, table and column names. Previous work has shown that filters can be created using a query paradigm focused on interaction with data tables. This paper presents a technique, Query-through-Drilldown, to enable join formulation in a data-oriented paradigm. Instead of formulating joins at the level of schemas, the user drills down through tables of data and the query is implicitly created based on the user's actions. Query-through-Drilldown has been applied to a large relational database, but similar techniques could be applied to semi-structured data or semantic web ontologies.