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Without a formal methodology extracting entities from business descriptions, a business requirement in the real world cannot be abstracted correctly into an entity-relationship schema. Once core entities are discovered, we can obtain an Entity-Relationship Diagram (ERD) by inserting relationships between/among the relevant entities and by aggregating some attributes into one of the entities or relationships. There have been so many studies on formal guidelines for extracting entities from business descriptions. Most of them adopt a knowledge-based approach which consults a knowledge base to recommend entity candidates. However, the knowledge-based approach usually fails to construct the most appropriate ERD for a given business domain. The approach performs the entity extraction on the stiff premise that an object would be classified as an entity if it happen to be classified as an entity once or more in past applications. The previous studies did not consider the flexibility in the object classification that even the same object could be regarded as either an entity or an attribute according to the various concerns of field workers. In this paper, we discuss some limitations of the previous researches on object classification and propose a new methodology for flexible entity extraction. To evaluate the practicality of the devised methodology, we developed a tool for the methodology and performed a case study on option trading applications with the tool.

Keywords: database design methodology, enterprise data modeling, entity-relationship model, requirements analysis, database design automation

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Received February 8, 2006; revised July 19 & August 31, 2006; accepted September 7, 2006.
Communicated by Ming-Syan Chen.