Abstract
Electronic Data Interchange (EDI) integration is crucial as it streamlines electronic data exchange between companies, enhancing efficiency and accuracy in business processes. This research aims to generate the corresponding target EDI format for given input data in a manner akin to the machine translation problem. The study explores various sequence-to-sequence models and encoder-decoder architectures to identify the most effective outcomes. The impact of these encoder-decoder and data input-output representation techniques on EDI integration is investigated using crowd-sourced datasets. The effectiveness of the proposed approach is demonstrated using different performance evaluation metrics. The findings revealed that using a Multi-Layer Seq2Seq model achieves an accuracy score of 90.21%, BLEU Score of 83.36% and ROUGE-L score of 88.5%, for enhancing EDI integration processes in businesses.
Original language | English |
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Title of host publication | Intelligent and Fuzzy Systems - Intelligent Industrial Informatics and Efficient Networks Proceedings of the INFUS 2024 Conference |
Editors | Cengiz Kahraman, Sezi Cevik Onar, Selcuk Cebi, Basar Oztaysi, Irem Ucal Sari, A. Cagrı Tolga |
Publisher | Springer Science and Business Media Deutschland GmbH |
Pages | 158-166 |
Number of pages | 9 |
ISBN (Print) | 9783031700170 |
DOIs | |
Publication status | Published - 2024 |
Event | International Conference on Intelligent and Fuzzy Systems, INFUS 2024 - Canakkale, Turkey Duration: 16 Jul 2024 → 18 Jul 2024 |
Publication series
Name | Lecture Notes in Networks and Systems |
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Volume | 1088 LNNS |
ISSN (Print) | 2367-3370 |
ISSN (Electronic) | 2367-3389 |
Conference
Conference | International Conference on Intelligent and Fuzzy Systems, INFUS 2024 |
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Country/Territory | Turkey |
City | Canakkale |
Period | 16/07/24 → 18/07/24 |
Bibliographical note
Publisher Copyright:© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Keywords
- Artificial Intelligence
- EDI Integration
- Natural Language Processing