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© 2019. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

[...]it is challenging for conventional qualitative review method to tackle the complex inherent heterogeneous of technology. [...]the above qualitative works are based solely on the literature review of the papers of specific machine tool technology or the analysis based on expert experience, but failed to conduct multi-dimensional collaborative exploration from various aspects, such as research, technology development and business. According to LDA, each multinomial distribution of topic φ→k follows a Dirichlet prior distribution with hyperparameters β→ : p(∅|β→)=Dir(φ→k|β→) , where both φ→k and β→ are V dimensional vectors. ∅ denotes a matrix with K×V dimension containing all topics’ multinomial distributions. φ→k,w denotes the probability of generating word w given topic k and it satisfies ∑wφ→k,w=1 , where w = 1, …, V. Then each word in document m can be generated by sampling from the corresponding multinomial distribution of latent assignment topic: p(wm,n|z=zm,n)=φ→zm,n . Given a document collection, wm,n is observable variable, α and β are prior hyper-parameters. zm,n,θ→m and φ→zm,n are hidden variables which can be estimated by the observed words in the corpus. [...]the introduction of emerging machine tool technologies to transform the traditional technologies in the machine tool domain and the development of green machine tools that save energy, reduce consumption and reduce environmental pollution is one of the key ways for the sustainable development of the machine tool industry in the future. [...]we perform a systematic analysis of multi-source scientific literature related to machine tool to explore its development from the multi-view perspectives of research, technology development and business mode.

Details

Title
Exploring the Development of Research, Technology and Business of Machine Tool Domain in New-Generation Information Technology Environment Based on Machine Learning
Author
Chen, Jihong; Zhang, Kai; Zhou, Yuan; Liu, Yufei; Li, Lingfeng; Chen, Zheng; Li, Yin
Publication year
2019
Publication date
2019
Publisher
MDPI AG
e-ISSN
20711050
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2322227387
Copyright
© 2019. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.