A logical design methodology for relational databases using the extended entity-relationship model
ACM Computing Surveys (CSUR)
A formal view integration method
SIGMOD '86 Proceedings of the 1986 ACM SIGMOD international conference on Management of data
A comparative analysis of methodologies for database schema integration
ACM Computing Surveys (CSUR)
ADDS: A system for automatic database schema design based on the binary-relationship model
Data & Knowledge Engineering
A methodology for creating user views in database design
ACM Transactions on Database Systems (TODS)
A rule-based approach for merging generalization hierarchies
Information Systems
A Generalized Expert System for Database Design
IEEE Transactions on Software Engineering
Conceptual schema and relational database design: a fact oriented approach
Conceptual schema and relational database design: a fact oriented approach
Federated database systems for managing distributed, heterogeneous, and autonomous databases
ACM Computing Surveys (CSUR) - Special issue on heterogeneous databases
Conceptual database design: an Entity-relationship approach
Conceptual database design: an Entity-relationship approach
A form-based approach for database analysis and design
Communications of the ACM
ACM Computing Surveys (CSUR)
Automated resolution of semantic heterogeneity in multidatabases
ACM Transactions on Database Systems (TODS)
Object models: strategies, patterns, applications
Object models: strategies, patterns, applications
International Journal of Human-Computer Studies - Special issue: the role of formal ontology in the information technology
CYC: a large-scale investment in knowledge infrastructure
Communications of the ACM
Database design with common sense business reasoning and learning
ACM Transactions on Database Systems (TODS)
An ontology-based expert system for database design
Data & Knowledge Engineering - Special issue on ER '97
Improving database design through the analysis of relationships
ACM Transactions on Database Systems (TODS)
Supporting reuse in systems analysis
Communications of the ACM
Naive Semantics for Natural Language Understanding
Naive Semantics for Natural Language Understanding
Naive Semantics to Support Automated Database Design
IEEE Transactions on Knowledge and Data Engineering
An Expert Database Design System Based on Analysis of Forms
IEEE Transactions on Software Engineering
A Method for Putting Strategic Common Sense into Expert Systems
IEEE Transactions on Knowledge and Data Engineering
Exploiting Domain Knowledge During the Automated Design of Object-Oriented Databases
ER '97 Proceedings of the 16th International Conference on Conceptual Modeling
Intelligent Support for Retrieval and Synthesis of Patterns for Object-Oriented Design
ER '97 Proceedings of the 16th International Conference on Conceptual Modeling
ER '98 Proceedings of the 17th International Conference on Conceptual Modeling
Naive Semantics to Support Automated Database Design
IEEE Transactions on Knowledge and Data Engineering
An Ontology for Classifying the Semantics of Relationships in Database Design
NLDB '00 Proceedings of the 5th International Conference on Applications of Natural Language to Information Systems-Revised Papers
Intelligent Database Design Diagnosis: Performance Assessment with the Provision of Domain Knowledge
Artificial Intelligence Review
Comparing Relationships in Conceptual Modeling: Mapping to Semantic Classifications
IEEE Transactions on Knowledge and Data Engineering
Data representation factors and dimensions from the quality function deployment (QFD) perspective
Journal of Information Science
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Although database design tools have been developed that attempt to automate (or semiautomate) the design process, these tools do not have the capability to capture common sense knowledge about business applications and store it in a context-specific manner. As a result, they rely on the user to provide a great deal of 驴trivial驴 details and do not function as well as a human designer who usually has some general knowledge of how an application might work based on his or her common sense knowledge of the real world. Common sense knowledge could be used by a database design system to validate and improve the quality of an existing design or even generate new designs. This requires that context-specific information about different database design applications be stored and generalized into information about specific application domains (e.g., pharmacy, daycare, hospital, university, manufacturing). Such information should be stored at the appropriate level of generality in a hierarchically structured knowledge base so that it can be inherited by the subdomains below. For this to occur, two types of learning must take place. First, knowledge about a particular application domain that is acquired from specific applications within that domain are generalized into a domain node (e.g., entities, relationships, and attributes from various hospital applications are generalized to a hospital node). This is referred to as within domain learning. Second, the information common to two (or more) related application domain nodes is generalized to a higher-level node; for example, knowledge from the car rental and video rental domains may be generalized to a rental node. This is called across domain learning. This paper presents a methodology for learning across different application domains based on a distance measure. The parameters used in this methodology were refined by testing on a set of representative cases; empirical testing provided further validation.