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Uma abordagem semiautomática para identificação de elementos de processo de negócio em texto de linguagem natural
| Content Provider | Semantic Scholar |
|---|---|
| Author | Ferreira, Renato César Borges |
| Copyright Year | 2017 |
| Abstract | To enable effective business process management, the first step is the design of appropriate process models to the organization’s objectives. These models are used to describe roles and responsibilities of the employees in an organizations. In addition, business process modeling is very important to report, understand and automate processes. However, the documentation existent in organizations about such processes is mostly unstructured and difficult to be understood by analysts. In this context, process modeling becomes highly time consuming and expensive, generating process models that do not comply with the reality of the organizations. The extracting of process models from textual descriptions may contribute to minimize the effort required in process modeling. In this context, this dissertation proposes a semi-automatic approach to identify process elements in natural language text. Based on the study of natural language processing, it was defined a set of mapping rules to identify process elements in text. In addition, in order to evaluate the mapping rules and to demonstrate the feasibility of the proposed approach, a prototype was developed able to identify process elements in text in a semiautomatic way. To measure the performance of the proposed prototype metrics were used to retrieve information such as precision, recall, and F-measure. In addition, two surveys were developed with the purpose of verifying the acceptance of the users. The evaluations present promising results. The analyses of 70 texts presented, on average, 73.61% precision, 70.15% recall and 71.82% F-measure. In addition, the results of the first and second surveys presented on average 91.66% acceptance of the participants. The main contribution of this work is to provide mapping rules for identify process elements in natural language text to support and minimize the time required for process modeling performed by process analysts. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://www.lume.ufrgs.br/bitstream/handle/10183/156635/001017520.pdf?isAllowed=y&sequence=1 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
