{"title":"探索在复杂设计中概括设计需求的主题建模","authors":"Cheng Chen, Beshoy Morkos","doi":"10.1080/09544828.2023.2268850","DOIUrl":null,"url":null,"abstract":"AbstractAs the redesign process progresses in product lifecycle management, effectively managing engineering changes becomes increasingly challenging, often leading to catastrophic and costly project failures. In response, the study provides a framework for generalising design requirements documents into topics that engineers can use to understand complex designs. Based on previous work, this study employs and compares four different models, including latent Dirichlet allocation (LDA), the collapsed Gibbs sampling algorithm for the Dirichlet multinomial mixtures model (GSDMM), LDA-BERT, and GSDMM-BERT to determine the appropriate representation of requirements documents. Both heatmaps and UMAPs are used to illustrate the correlation between topics and words. The results indicate that the combined vector representation of topic modelling and the sentence-BERT model outperforms single topic modelling. This combined model leverages the additional knowledge from a pre-trained sentence-BERT model, thereby improving model performance and word distribution in all three industrial projects. Through this proposed framework, engineers can potentially generalise high-quality requirements topics for large requirements documents.KEYWORDS: Requirement managementrequirement topicscomplex designBERTdesign process Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1 https://radimrehurek.com/gensim/models/ldamodel.html2 https://docs.scipy.org/doc/scipy/reference/generated/scipy.spatial.distance.pdist.html","PeriodicalId":50207,"journal":{"name":"Journal of Engineering Design","volume":"20 1","pages":"0"},"PeriodicalIF":2.5000,"publicationDate":"2023-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Exploring topic modelling for generalising design requirements in complex design\",\"authors\":\"Cheng Chen, Beshoy Morkos\",\"doi\":\"10.1080/09544828.2023.2268850\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"AbstractAs the redesign process progresses in product lifecycle management, effectively managing engineering changes becomes increasingly challenging, often leading to catastrophic and costly project failures. In response, the study provides a framework for generalising design requirements documents into topics that engineers can use to understand complex designs. Based on previous work, this study employs and compares four different models, including latent Dirichlet allocation (LDA), the collapsed Gibbs sampling algorithm for the Dirichlet multinomial mixtures model (GSDMM), LDA-BERT, and GSDMM-BERT to determine the appropriate representation of requirements documents. Both heatmaps and UMAPs are used to illustrate the correlation between topics and words. The results indicate that the combined vector representation of topic modelling and the sentence-BERT model outperforms single topic modelling. This combined model leverages the additional knowledge from a pre-trained sentence-BERT model, thereby improving model performance and word distribution in all three industrial projects. Through this proposed framework, engineers can potentially generalise high-quality requirements topics for large requirements documents.KEYWORDS: Requirement managementrequirement topicscomplex designBERTdesign process Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1 https://radimrehurek.com/gensim/models/ldamodel.html2 https://docs.scipy.org/doc/scipy/reference/generated/scipy.spatial.distance.pdist.html\",\"PeriodicalId\":50207,\"journal\":{\"name\":\"Journal of Engineering Design\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2023-10-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Engineering Design\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/09544828.2023.2268850\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Engineering Design","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/09544828.2023.2268850","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
Exploring topic modelling for generalising design requirements in complex design
AbstractAs the redesign process progresses in product lifecycle management, effectively managing engineering changes becomes increasingly challenging, often leading to catastrophic and costly project failures. In response, the study provides a framework for generalising design requirements documents into topics that engineers can use to understand complex designs. Based on previous work, this study employs and compares four different models, including latent Dirichlet allocation (LDA), the collapsed Gibbs sampling algorithm for the Dirichlet multinomial mixtures model (GSDMM), LDA-BERT, and GSDMM-BERT to determine the appropriate representation of requirements documents. Both heatmaps and UMAPs are used to illustrate the correlation between topics and words. The results indicate that the combined vector representation of topic modelling and the sentence-BERT model outperforms single topic modelling. This combined model leverages the additional knowledge from a pre-trained sentence-BERT model, thereby improving model performance and word distribution in all three industrial projects. Through this proposed framework, engineers can potentially generalise high-quality requirements topics for large requirements documents.KEYWORDS: Requirement managementrequirement topicscomplex designBERTdesign process Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1 https://radimrehurek.com/gensim/models/ldamodel.html2 https://docs.scipy.org/doc/scipy/reference/generated/scipy.spatial.distance.pdist.html
期刊介绍:
The Journal of Engineering Design is a leading international publication that provides an essential forum for dialogue on important issues across all disciplines and aspects of the design of engineered products and systems. The Journal publishes pioneering, contemporary, best industrial practice as well as authoritative research, studies and review papers on the underlying principles of design, its management, practice, techniques and methodologies, rather than specific domain applications.
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