Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Formal Concept Analysis: Mathematical Foundations
Formal Concept Analysis: Mathematical Foundations
Numerical Aspects in the Data Model of Conceptual Information Systems
ER '98 Proceedings of the Workshops on Data Warehousing and Data Mining: Advances in Database Technologies
TOSCANA - a Graphical Tool for Analyzing and Exploring Data
GD '94 Proceedings of the DIMACS International Workshop on Graph Drawing
Towards a Temporal Extension of Formal Concept Analysis
AI '01 Proceedings of the 14th Biennial Conference of the Canadian Society on Computational Studies of Intelligence: Advances in Artificial Intelligence
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Conceptual Information Systems unfold the conceptual structure of data stored in relational databases. In the design phase of the system, conceptual hierarchies have to be created which describe different aspects of the data. In this paper, we describe two principal ways of designing such conceptual hierarchies, data driven design and theory driven design, and discuss advantages and drawbacks. The central part of the paper shows how Attribute Exploration, a knowledge acquisition tool developed by B. Ganter can be applied for narrowing the gap between both approaches.