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检索条件"任意字段=7th International Conference on Data Mining and Big Data, DMBD 2022"

共 1004 条记录，以下是11-20 订阅

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2022 7th international conference on Cloud Computing and big data Analytics [Front cover]

2022 7th International Conference on Cloud Computing and Big...

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IEEE international conference on Cloud Computing and big data Analysis (ICCCBDA)

Presents the front cover or splash screen of the proceedings record.

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FS-IGA: Feature Selection Method Based on Improved Genetic Algorithm 7th

FS-IGA: Feature Selection Method Based on Improved Genetic A...

引用

8th Asia Pacific Web and Web-Age Information Management Joint international conference on Web and big data

作者： Li, Dong Du, Shumei Wei, Yong Qin, Lei Du, Yuefeng Liaoning Univ Shenyang 110036 Peoples R China

ISBN: (纸本)9789819600540;9789819600557

Feature selection is one of the important techniques of machine learning and data mining. However, with the continuous growth of data scale and application scenarios, the traditional feature selection methods have some defects. In this paper, a Feature Selection method based on Improved Genetic Algorithm (FS-IGA) is proposed. Firstly, the fitness function is improved by introducing the separability criterion based on the distance between classes. Secondly, the decision tree is introduced as the classifier in the genetic algorithm to optimize the performance of the algorithm. Finally, experimental results show that our proposed method can effectively improve the accuracy and adaptability of feature selection. the method presented in this paper boasts of a unique advantage in that it transcends reliance on any specific model framework, thereby ensuring broader applicability. As such, this paper provides a more profound reference value for the research on feature selection in the field of machine learning and data mining.

关键词： Genetic Algorithm Feature Selection Decision Tree Machine Learning data mining

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Research on Intelligent mining Methods of Teaching data for Economics and Management Specialties in Colleges and Universities in the Context of Industry-Teaching Integration 24

Research on Intelligent Mining Methods of Teaching Data for ...

引用

7th international conference on Educational Technology Management, ICETM 2024

作者： Wang, Fang Xun, Xun College of Management Changchun University of Architecture Jilin Changchun China

ISBN: (纸本)9798400717468

In order to improve the teaching quality, an intelligent technology is explored to extract insights from the teaching data of economics and management. Under the framework of the integration of education industry, this paper makes a comprehensive analysis of the composition of teaching data of economics and management majors in Colleges and universities. the analysis includes teaching content, student statistics and teacher profiles. the resulting composition is represented in a data matrix format. then the dissimilarity matrix is calculated, and the Euclidean distance measurement is used to effectively classify and cluster the teaching data. In the mining stage, the decision tree is used to analyze the clustering teaching data. the analysis uses a window that contains both positive examples (the teaching data has a good correlation with the educational objectives of the economic management major in Colleges and universities) and negative examples (the teaching data has a negative correlation with these objectives). through the test, the application of design mining results not only stabilized the realization of the four teaching objectives at about 9.0 points (10 points system), but also improved the overall evaluation score of the teaching objectives to 36.57 points. © 2024 Copyright held by the owner/author(s).

关键词： Decision tree

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Enhancing Student Outcomes through Educational big data and data mining: A Systematic Literature Review

Enhancing Student Outcomes Through Educational Big Data and ...

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7th international conference on Industrial and Logistics Systems, SIL 2024

作者： Afif, Fatima-Ezzahra Bouyahia, Fatima Rafouk, Leila Laboratory of Didactic and University Pedagogy Cadi Ayyad University Marrakesh Morocco Laboratory of Engineering and Systems Analysis Cadi Ayyad University Marrakesh Morocco

ISBN: (纸本)9783031873089

the world is changing at rapid rhythm, the rise of digital technologies such as big data, artificial intelligence, simulation… is creating drastic innovations and new opportunities for learning and development. this is leading to the 4th industrial revolution known as Industry 4.0, which is hugely changing the world of work. As a result, traditional teaching models are becoming obsolete, so it would be essential to rethink and customize the processes of information generation and transfer to make them more efficient and flexible. big data has emerged as a game-changer in various industries, and education is no exception. the collection and analysis of large datasets, known as educational big data, have paved the way for innovative approaches in tracking student progress, identifying at-risk students, and enhancing teaching and learning. this data is mined and analyzed through the Educational data mining (EDM), a cross-disciplinary field involving computer science, education and statistics. It analyses and mines education related data to better understand students and setting which they learn. EDM focuses on developing new tools and algorithms for discovering data patterns, making data driving decision and solving various types of educational problems. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Students

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Resource Allocation for Civil Aviation Security Job Competency Course Reform Based on big data Multimedia Technology 24

Resource Allocation for Civil Aviation Security Job Competen...

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7th international conference on Educational Technology Management, ICETM 2024

作者： Wang, Jing Ma, Chunting Huang, Tianxiang Sanya Aviation and Tourism College Hainan Sanya China

ISBN: (纸本)9798400717468

the conventional resource allocation method for civil aviation security post competency course reform is based on post elements, and the allocated resources are more considering the post level, which can not meet the adaptability demand of resource allocation. therefore, a resource allocation method based on big data multimedia technology is designed for the reform of civil aviation security post competency course. We determine the set of big data cluster elements for resource allocation of security inspection job competency course, and deeply understand the connotation of civil aviation security inspection job competency, so as to adjust the resource allocation strategy at any time. Based on the big data multimedia technology, we construct a resource allocation model for the reform of security inspection job competency course, collect data related to security inspection job competency, and comprehensively assess the job competency. the optimal parameters of resource allocation for the reform of civil aviation security post competency course are adjusted to adapt to multiple course reform scenarios by adjusting the type, quantity and quality of course resources, the skill level, learning speed and willingness to learn of the security personnel, as well as the duration, frequency and mode of the training courses. Comparative experiments are used to verify that the method is more effective in resource allocation and can be applied in real life. © 2024 Copyright held by the owner/author(s).

关键词： Civil aviation

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7th international conference on Industrial and Logistics Systems, SIL 2024

7th International Conference on Industrial and Logistics Sys...

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7th international conference on Industrial and Logistics Systems, SIL 2024

ISBN: (纸本)9783031873089

the proceedings contain 19 papers. the special focus in this conference is on Industrial and Logistics Systems. the topics include: Port Community Systems and Organizational Performance: A Socio-technical Approach to Evaluation;Study of the Impact of Lean Management Tools and the IATF Automotive Standard on Product and Process Quality Management;implementation of 5S Lean Tool in a Higher Education Institution;Cutting Parameters of Milling Process Optimization to Minimize Material Removal Power for AISI 1045 Steel;Transforming Maintenance Performance through Lean-TRIZ;driving Lean Practices to Improve Procurement in Supply Chains through Industry 4.0;Designing Sustainable Products to Satisfy Customer Needs and Reduce Environmental Impact: A Systematic Review of the ANP-QFD-LCA Approach to Sustainable Innovation;ISO 14001 Certification as a Strategic Means of Decarbonization: A Multi-Case Study Investigation;agri-Food Supply Chain Under Labor Constraints and Blockchain Technology;the Blockchain Technology for Financial Inclusion of Smallholder Farmers in Africa;a Machine Learning Approach Based on Contract Parameters for Cost Forecasting in Construction;empowering Industry 5.0 Supply Chain: Insights from a Systematic Literature Review of Digital Maturity Models;exploring the Transition from Maintenance 4.0 Towards Maintenance 5.0: A Systematic Literature Review;enhancing Student Outcomes through Educational big data and data mining: A Systematic Literature Review;managers’ Insights on Industry 4.0: Benefits, Strategies and Obstacles;the Transformative Role of ML Algorithms in Supply Chain Management: A Systematic Literature Review.

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Using a new threshold function in seismic data de-noising 7

Using a new threshold function in seismic data de-noising

引用

2024 7th international Workshop on Environment and Geoscience, IWEG 2024

作者： Qin, Feilong Cheng, Yali Zhu, Hongjin School of Big Data and Artificial Intelligence Chengdu Technological University Chengdu611730 China

In geological exploration, there is a large amount of unpredictable noise interference in seismic data that needs to be removed. the traditional soft and hard threshold methods have been widely used in seismic data de-noising, but they have some defects such as discontinuity and constant deviation at the threshold, which leads to poor de-noising effects. therefore, this paper introduces the weighted average idea into the traditional threshold methods and an improved threshold function based on seismic data de-noising is proposed. In the new method, this paper explores the layers of wavelet decomposition, establishes an optimal wavelet basis, and selects a variability threshold according to the number of decomposition layers instead of a fixed constant, avoiding the elimination of some effective signals. the de-noising effect of new method is evaluated by using two evaluation indicators: signal-to-noise ratio abbreviated as SNR and root mean square error abbreviated as RMSE. Finally, the designed new method is applied to actual mining areas for seismic data de-noising. the results show that the new method can effectively remove noise from seismic data and the texture of seismic profile after noise reduction is clear and smooth. Compared with traditional threshold methods, the new method has better de-noising performance. © Published under licence by IOP Publishing Ltd.

关键词： Wavelet decomposition

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Analysis of the Situation and Countermeasures of College English CET-4 and CET-6 Exams in Chinese Higher Vocational Colleges under big data-A Case Study of Guangdong Polytechnic Institute 24

Analysis of the Situation and Countermeasures of College Eng...

引用

7th international conference on Educational Technology Management, ICETM 2024

作者： Hou, Haibing Huang, Jiesheng Guangdong Open University Guangdong Polytechnic Institute Guangdong Guangzhou China

ISBN: (纸本)9798400717468

With the deepening of global internationalization, the application scope of the English language is becoming increasingly widespread. As national English examinations organized by the Ministry of Education Examination Center, the College English Test Band 4 and Band 6 (CET-4 and CET-6) scores are not only one of the important standards for measuring students’ English proficiency but also significantly influence their academic development and career prospects. Taking Guangdong Polytechnic Institute as an example, this study first analyzes the current pass rates of CET-4 and CET-6 exams in Chinese higher vocational colleges through big data research. Based on the analysis results, several countermeasures are proposed, followed by a discussion on the washback effect of these exams. the data indicate that listening, reading, and writing are all critical modules affecting the pass rates of CET-4 and CET-6 exams, with listening scores being relatively satisfactory while reading and writing scores are generally low. the study proposes several washback strategies, such as adhering to the language learning principle of"listening and speaking first, followed by reading and writing," emphasizing sustainable language development abilities, leveraging AI to empower foreign language teaching, achieving the unification of applicability and timeliness in college English courses, breaking down inter-departmental barriers, expanding international development channels for various departments, and building a diversified platform for communication and cooperation. Schools should maximize the positive washback effects of CET-4 and CET-6 exams and minimize negative impacts by employing diversified teaching methods and reasonable assessment systems to comprehensively enhance students’ overall English proficiency. © 2024 Copyright held by the owner/author(s).

关键词： Apprentices

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2024 7th international conference on Artificial Intelligence and big data, ICAIBD 2024

2024 7th International Conference on Artificial Intelligence...

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7th international conference on Artificial Intelligence and big data, ICAIBD 2024

ISBN: (纸本)9798350385106

the proceedings contain 98 papers. the topics discussed include: patient clustering to improve process mining for disease trajectory analysis using Indonesia health insurance dataset;a comprehensive review of transformer-based models: ChatGPT and bard in focus;pneumonia image classification: deep learning and machine learning fusion;exploring the pathways to optimize immersive imaging experiences using AIGC technology;sentiment analysis of song dynasty classical poetry using fine-tuned large language models: a study with LLMs;a random forest stock prediction model based on Bayesian optimization;multi-level generative pretrained transformer for improving malware detection performance;and research on building a competency model for managers in private express enterprises based on recruitment big data.

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2021 IEEE 23rd international conference on High Performance Computing and Communications, 7th international conference on data Science and Systems, 19th international conference on Smart City and 7th international conference on Dependability in Sensor, Cloud and big data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

2021 IEEE 23rd International Conference on High Performance ...

引用

23rd IEEE international conference on High Performance Computing and Communications, 7th IEEE international conference on data Science and Systems, 19th IEEE international conference on Smart City and 7th IEEE international conference on Dependability in Sensor, Cloud and big data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

ISBN: (纸本)9781665494571

the proceedings contain 343 papers. the topics discussed include: three-level compact caching for search engines based on solid state drives;a fine-grained volley gesture recognition method with direction independence;universal adversarial attack against 3d object tracking;efficient hardware redo logging for secure persistent memory;a cost-efficient metadata scheme for high-performance deduplication systems;high speed true random number generator controlled by logistic map;characterization and implication of edge WebAssembly runtimes;frend for edge servers: reduce server number! keeping service quality!;on-the-fly servers placement for online multiplayer games in the fog;advanced architecture design of high-radix router based on chiplet integration and IP reusability;embrace the conflicts: exploring the integration of single port memory in systolic array-based accelerators;visual sensitivity aware rate adaptation for video streaming via deep reinforcement learning;semi-supervised federated learning with non-IID data: algorithm and system design;on-demand intelligent routing algorithms for the deterministic networks;and distributed service placement in ultra-dense edge computing: a game-theoretical approach.

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