Heuristic-based entity-relationship modelling through natural language processing

N Omar, JRP Hanna, P McKevitt

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abstract

Here we propose new heuristics that assist the semi-automated generation of Entity-Relationship (ER) diagrams for database modelling from a natural language description and describe 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 95% recall and 82% precision. 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.
Original languageEnglish
Title of host publicationUnknown Host Publication
EditorsL McGinty, B Crean
Place of PublicationDublin, Ireland
PublisherArtificial Intelligence Association of Ireland
Pages302-313
Number of pages12
ISBN (Print)1-902277-89-9
Publication statusPublished - Sep 2004
EventProc. of the 15th Artificial Intelligence and Cognitive Science Conference (AICS-04) - Galway-Mayo Institute of Technology (GMIT), Castlebar, Ireland
Duration: 1 Sep 2004 → …

Conference

ConferenceProc. of the 15th Artificial Intelligence and Cognitive Science Conference (AICS-04)
Period1/09/04 → …

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    Omar, N., Hanna, JRP., & McKevitt, P. (2004). Heuristic-based entity-relationship modelling through natural language processing. In L. McGinty, & B. Crean (Eds.), Unknown Host Publication (pp. 302-313). Artificial Intelligence Association of Ireland. http://www.4c.ucc.ie/aiai/