Semantic analysis in the automation of ER modelling through natural language processing

N Omar; JRP Hanna; P McKevitt

doi:10.1109/ICOCI.2006.5276559

Semantic analysis in the automation of ER modelling through natural language processing

N Omar, JRP Hanna, P McKevitt

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Citations (Scopus)

149 Downloads (Pure)

Abstract

This paper deals with the problem of extracting semantic knowledge in the production of ER models from natural language specifications. The application of semantic heuristics is proposed as the strategy to obtain the relevant ER elements such as entities, attributes and relationships from the specifications. Earlier research has shown that syntactic heuristics produced good results in identifying the relevant and correct results of the ER elements in terms of recall and precision. The inclusion of the semantic lexical knowledge is hoped to further improve the results. The semantic heuristics may later be implemented as part of a natural language tool in the generation of the ER models.

Original language	English
Title of host publication	Unknown Host Publication
Place of Publication	Tokyo, Japan
Publisher	IEEE Computer Society
Pages	1-5
Number of pages	5
ISBN (Print)	978-1-4244-0219-9
DOIs	https://doi.org/10.1109/ICOCI.2006.5276559
Publication status	Published (in print/issue) - Jun 2006
Event	Proc. of the IEEE International Conference on Computing and Informatics (ICOCI-2006) - Legend Hotel, Kuala Lumpur, Malaysia Duration: 1 Jun 2006 → …

Conference

Conference	Proc. of the IEEE International Conference on Computing and Informatics (ICOCI-2006)
Period	1/06/06 → …

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10.1109/ICOCI.2006.5276559

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title = "Semantic analysis in the automation of ER modelling through natural language processing",

abstract = "This paper deals with the problem of extracting semantic knowledge in the production of ER models from natural language specifications. The application of semantic heuristics is proposed as the strategy to obtain the relevant ER elements such as entities, attributes and relationships from the specifications. Earlier research has shown that syntactic heuristics produced good results in identifying the relevant and correct results of the ER elements in terms of recall and precision. The inclusion of the semantic lexical knowledge is hoped to further improve the results. The semantic heuristics may later be implemented as part of a natural language tool in the generation of the ER models.",

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AB - This paper deals with the problem of extracting semantic knowledge in the production of ER models from natural language specifications. The application of semantic heuristics is proposed as the strategy to obtain the relevant ER elements such as entities, attributes and relationships from the specifications. Earlier research has shown that syntactic heuristics produced good results in identifying the relevant and correct results of the ER elements in terms of recall and precision. The inclusion of the semantic lexical knowledge is hoped to further improve the results. The semantic heuristics may later be implemented as part of a natural language tool in the generation of the ER models.

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ER -

Semantic analysis in the automation of ER modelling through natural language processing

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