Understanding Quality in Conceptual Modeling
IEEE Software
Conceptual schema analysis: techniques and applications
ACM Transactions on Database Systems (TODS)
The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Entity-Relationship Modeling: Foundations of Database Technology
Entity-Relationship Modeling: Foundations of Database Technology
Automated abstraction of class diagrams
ACM Transactions on Software Engineering and Methodology (TOSEM)
Extending ER Model Clustering by Relationship Clustering
ER '93 Proceedings of the 12th International Conference on the Entity-Relationship Approach: Entity-Relationship Approach
A Methodology for Clustering Entity Relationship Models - A Human Information Processing Approach
ER '99 Proceedings of the 18th International Conference on Conceptual Modeling
Conceptual modelling of web information systems
Data & Knowledge Engineering
Modeling events as entities in object-oriented conceptual modeling languages
Data & Knowledge Engineering - Special issue: ER 2004
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Conceptual Modeling of Information Systems
Conceptual Modeling of Information Systems
Summarizing relational databases
Proceedings of the VLDB Endowment
Usability of upper level ontologies: The case of ResearchCyc
Data & Knowledge Engineering
Improving the Usability of HL7 Information Models by Automatic Filtering
SERVICES '10 Proceedings of the 2010 6th World Congress on Services
A method for filtering large conceptual schemas
ER'10 Proceedings of the 29th international conference on Conceptual modeling
How to tame a very large ER diagram (using link analysis and force-directed drawing algorithms)
ER'05 Proceedings of the 24th international conference on Conceptual Modeling
Rigorous Methods for Software Construction and Analysis
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The visualization and the understanding of large conceptual schemas require the use of specific methods. These methods generate clustered, summarized or focused schemas that are easier to visualize and to understand. All of these methods require computing the importance of the elements in the schema but, up to now, only the importance of entity types has been taken into account. In this paper, we present three methods for computing the importance of associations by taking into account the knowledge defined in the structural and behavioral parts of the schema. We experimentally evaluate these methods with large real-world schemas and present the main conclusions we have drawn from the experiments.