Overview Machine Learning and Deep Learning Frameworks

Liermann, Volker

doi:10.1007/978-3-030-78821-6_12

Cited by 6 publications

(2 citation statements)

References 8 publications

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“…Grounded on the investigation results of experts and academics, combined with the unique characteristics of college students' entrepreneurship in China, this paper analyzes and investigates the risk assessment features and elements of institutional apprentices' entrepreneurship and establishes the index structure framework of initial college students' entrepreneurial risk factors, which includes four dimensions: entrepreneurial environment, school education, core team, and entrepreneurs, that is, the index framework of initial college students' entrepreneurial risk assessment includes four (4) first-level signs and approximately 31 second-level pointers. In the next stage, we get the ranking list of college students' entrepreneurial risk assessment under the entrepreneurial practice environment and see Tables 1 and 2 for the distribution framework of college students' entrepreneurial risk factors under the entrepreneurial practice environment [11].…”

Section: Characteristics and Distribution Of College Students' Entrep...mentioning

confidence: 99%

Research on the College Students’ Venture Risk Assessment Model Based on the LightGBM Algorithm

Feng

Zhang

2022

Mobile Information Systems

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There are numerous risk factors in the school students’ entrepreneurial process. In order to advance the accuracy of school students’ entrepreneurial risk assessment within entrepreneurial practice background and reduce risk management factors, a model of school students’ entrepreneurial risk assessment grounded on the LightGBM algorithm is proposed. We construct the statistical probability density distribution and constraint parameter model of college students’ entrepreneurial risk distribution in an entrepreneurial practice environment. Moreover, we adopt the factor hierarchical classification technology of the evaluation index system to realize the framework model construction and big data fusion processing of college students’ entrepreneurial risk indicators in the entrepreneurial practice environment. Then, we extract the joint similarity feature set of college students’ entrepreneurial risk factors in the entrepreneurial practice environment and adopt the LightGBM feature detection and fuzzy matching technology. The self-adaptive optimization and fuzzy clustering analysis are realized in the procedure of school students’ entrepreneurial risk assessment under the entrepreneurial practice environment, and a fuzzy Bayesian network assessment model for school students’ entrepreneurial risk assessment under the entrepreneurial practice environment is constructed. The Delphi method is used to determine the pairwise influence relationship between factors, and the LightGBM algorithm is used to optimize the evaluation of college students’ entrepreneurial risk factors under the entrepreneurial practice environment and match rough set features. According to the comprehensive evaluation of entrepreneurial risk factors, the intelligent entrepreneurial risk assessment under the entrepreneurial practice environment is comprehended. The simulation outcomes confirm that the intelligence of college students’ entrepreneurial risk assessment in the entrepreneurial practice environment is improved, and the precision of risk assessment is greater than other approaches.

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Section: Characteristics and Distribution Of College Students' Entrep...mentioning

confidence: 99%

Research on the College Students’ Venture Risk Assessment Model Based on the LightGBM Algorithm

Feng

Zhang

2022

Mobile Information Systems

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“…To analyze international students' needs and perceptions, and grouping them into categories [69], Adriana et al [70] proposed a probabilistic topic model approach using LDA. The authors used a machine learning for language toolkit (MALLET) [71] to run LDA and selected 20 topics based on 59,662 reviews. The topics covered in the research were language skills, convenient accommodation, weather, academic burdens, interesting courses and so on.…”

Section: ) Non-probabilistic Modelsmentioning

confidence: 99%

A Review of the Trends and Challenges in Adopting Natural Language Processing Methods for Education Feedback Analysis

Shaik

Tao

et al. 2022

IEEE Access

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Artificial Intelligence (AI) is a fast-growing area of study that stretching its presence to many business and research domains. Machine learning, deep learning, and natural language processing (NLP) are subsets of AI to tackle different areas of data processing and modelling. This review article presents an overview of AI's impact on education outlining with current opportunities. In the education domain, student feedback data is crucial to uncover the merits and demerits of existing services provided to students. AI can assist in identifying the areas of improvement in educational infrastructure, learning management systems, teaching practices and study environment. NLP techniques play a vital role in analyzing student feedback in textual format. This research focuses on existing NLP methodologies and applications that could be adapted to educational domain applications like sentiment annotations, entity annotations, text summarization, and topic modelling. Trends and challenges in adopting NLP in education were reviewed and explored. Contextbased challenges in NLP like sarcasm, domain-specific language, ambiguity, and aspect-based sentiment analysis are explained with existing methodologies to overcome them. Research community approaches to extract the semantic meaning of emoticons and special characters in feedback which conveys user opinion and challenges in adopting NLP in education are explored.

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LuoJiaAI: A cloud-based artificial intelligence platform for remote sensing image interpretation

Zhang

Gong

et al. 2023

Geo-spatial Information Science

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Overview Machine Learning and Deep Learning Frameworks

Cited by 6 publications

References 8 publications

Research on the College Students’ Venture Risk Assessment Model Based on the LightGBM Algorithm

Research on the College Students’ Venture Risk Assessment Model Based on the LightGBM Algorithm

A Review of the Trends and Challenges in Adopting Natural Language Processing Methods for Education Feedback Analysis

LuoJiaAI: A cloud-based artificial intelligence platform for remote sensing image interpretation

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