Automatic Detection and Resolution of Lexical Ambiguity in Process Models
| Autor: | Henrik Leopold, Fabian Pittke, Jan Mendling |
|---|---|
| Přispěvatelé: | Software and Sustainability (S2) |
| Rok vydání: | 2015 |
| Předmět: |
Lexical choice
business.industry Computer science Process (engineering) Synonym media_common.quotation_subject Lexical ambiguity Context (language use) Ambiguity Work in process computer.software_genre Homonym Artificial intelligence business computer Software Natural language processing Natural language media_common |
| Zdroj: | Pittke, F, Leopold, H & Mendling, J 2015, ' Automatic Detection and Resolution of Lexical Ambiguity in Process Models ', IEEE Transactions on Software Engineering . https://doi.org/10.1109/TSE.2015.2396895 IEEE Transactions on Software Engineering. Institute of Electrical and Electronics Engineers Inc. |
| ISSN: | 1939-3520 0098-5589 |
| DOI: | 10.1109/tse.2015.2396895 |
| Popis: | System-related engineering tasks are often conducted using process models. In this context, it is essential that these models do not contain structural or terminological inconsistencies. To this end, several automatic analysis techniques have been proposed to support quality assurance. While formal properties of control flow can be checked in an automated fashion, there is a lack of techniques addressing textual quality. More specifically, there is currently no technique available for handling the issue of lexical ambiguity caused by homonyms and synonyms. In this paper, we address this research gap and propose a technique that detects and resolves lexical ambiguities in process models. We evaluate the technique using three process model collections from practice varying in size, domain, and degree of standardization. The evaluation demonstrates that the technique significantly reduces the level of lexical ambiguity and that meaningful candidates are proposed for resolving ambiguity. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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