Acquisition of entity-relationship models from natural language specifications using heuristics
Year: 2005
Type: conference-paper
Abstract: This paper describes a heuristics-based approach in the semi-automated generation of Entity-Relationship (ER) diagrams for database modelling from natural language specifications and describes the implementation of such a system called ER-Converter.Though this is a semi-automatic transformation process, ER-Converter aims to require minimal human intervention during the process.ER-Converter has been evaluated in blind trials against a set of database problems.ER-Converter has an average of 90% recall and 85% precision.In terms of user intervention, ER-Converter requires very little human assistance with only 1.6% in the test dataset.The evaluation results are discussed and demonstrate that ER-Converter could be used, for example, within the domain model of a multimedia intelligent tutoring system, designed to assist in the learning and teaching of databases.
Authors: Nazlia Omar, Paul R. Hanna, Paul McKevitt
Institution: National University of Malaysia
Language: English
Subfield: Software
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2267943897