@inproceedings{52ce9e7318d5449982f3d8ee222e44b3,
title = "Bidirectional Long Short-Term Memory for Entailment Identification in Requirement Specifications Using Information from Use Case Diagrams",
abstract = "Text entailment is a field of natural language processing research that concerned with understanding the meanings or semantics of sentences or text fragments. An entailment statement is a relationship between sentences where the truth of one sentence necessarily implies the truth of another. In requirements engineering (RE), identifying entailments between requirements is crucial for modeling the dependencies. Current entailment methods are not suitable for this purpose. This research proposes a new architecture for classifying entailments between requirements in the software specification document. The proposed architecture builds a training model using use case diagram and its description. The training model is later used for classifying entailments between requirements statements. Based on the case study, the training model can identify entailments between requirement statements.",
keywords = "BiLSTM, Software specification document, Text entailment, Use case diagram",
author = "Firmawan, {Dony Bahtera} and Daniel Siahaan",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2021 International Seminar on Machine Learning, Optimization, and Data Science, ISMODE 2021 ; Conference date: 29-01-2022",
year = "2022",
doi = "10.1109/ISMODE53584.2022.9743037",
language = "English",
series = "2021 International Seminar on Machine Learning, Optimization, and Data Science, ISMODE 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "331--336",
booktitle = "2021 International Seminar on Machine Learning, Optimization, and Data Science, ISMODE 2021",
address = "United States",
}