2018
DOI: 10.1016/j.eswa.2017.09.002
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Knowledge extraction and visualization of digital design process

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Cited by 21 publications
(6 citation statements)
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“…Since meaningful terms are made of two or more words (Tseng, Lin, and Lin 2007; Fantoni et al 2013), it is critically important to identify these before applying higher-level NLP tasks. Scholars have resorted to ontology-based approaches to identify these terms (Yang et al 2018; Fantoni et al 2021). While ontology-based approaches are recommended over common-sense lexicon (e.g., WordNet), it is necessary to rely on domain-specific language models and generic- design- and technical-oriented lexicon to identify general terms (e.g., rough surface).…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…Since meaningful terms are made of two or more words (Tseng, Lin, and Lin 2007; Fantoni et al 2013), it is critically important to identify these before applying higher-level NLP tasks. Scholars have resorted to ontology-based approaches to identify these terms (Yang et al 2018; Fantoni et al 2021). While ontology-based approaches are recommended over common-sense lexicon (e.g., WordNet), it is necessary to rely on domain-specific language models and generic- design- and technical-oriented lexicon to identify general terms (e.g., rough surface).…”
Section: Discussionmentioning
confidence: 99%
“…Arnarsson et al (2021) use latent dirichlet allocation (LDA) to cluster the Doc2Vec-based embeddings of over 8000 Engineering Change Requests (ECRs) in a commercial vehicle manufacturer. Yang et al (2018) construct an ontology using 114,793 problem-solution records within preassembly reports inside an automotive manufacturer. They use the ontology to process (e.g., identify n-grams), structure and represent new text data in various forms (2018, p. 214) to facilitate the design and managerial decisions.…”
Section: Reviewmentioning
confidence: 99%
“…Hidden Markov Model, Maximum Entropy Markov Model and Conditional Random Field are widely used sequential labeling models. Work on knowledge discovery using text mining technique (Yang et al, 2018) defines a domain ontology and then, using that ontology carries out the knowledge extraction along with data visualization. Illustrative results are obtained using a corpus of 140,000 technical reports.…”
Section: Information Extractionmentioning
confidence: 99%
“…Knowledge extraction is the stage of extracting information from data to be used as knowledge (Gangemi et al, 2016;Yang et al, 2018). All stages of this extraction are using RapidMiner Studio software.…”
Section: Knowledge Extractionmentioning
confidence: 99%