文章基本信息

标题：Machine Learning Methods for Inferring Interaction Design Patterns from Textual Requirements
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作者：Viridiana Silva-Rodríguez ; Sandra Edith Nava-Muñoz ; Luis A. Castro 等
期刊名称：Proceedings
电子版ISSN：2504-3900
出版年度：2019
卷号：31
期号：1
页码：26
DOI：10.3390/proceedings2019031026
语种：English
出版社：MDPI AG
摘要：Ambient intelligence is one of the most exciting fields of application for pervasive, wireless, and embedded computing. However, the design and implementation of real-world systems must be conducted utilizing software engineering approaches. Some types of environments (hospitals, older adults homes, emergency scenarios, etc.) are particularly critical, especially in terms of the issues concerning expressing requirements, verifying and validating them, or ensuring functional correctness. To provide adequate ambient intelligence solutions, it is necessary to place special emphasis on obtaining, specifying, and documenting software requirements. To address this issue, our paper presents a model that integrates both requirements and design patterns. This is done through a natural language processing application in conjunction with other artificial intelligence algorithms. This work aims to support designers when analyzing text requirements and support design decisions. Our results were evaluated according to the cross-validated accuracy of predicting design patterns. The results obtained indicate that this approach could lead to good recommendations of design patterns, as it demonstrated an acceptable classification performance over the balanced dataset of requirements instances.