Proceedings of the 2022 3rd International Symposium on Big Data and Artificial Intelligence最新文献_第2页

Financial data processing and forecasting model analysis based on neural network 基于神经网络的财务数据处理与预测模型分析

Proceedings of the 2022 3rd International Symposium on Big Data and Artificial Intelligence Pub Date : 2022-12-09 DOI: 10.1145/3598438.3598445

Wenjie Xiong, U. Comite

引用次数: 0

A study of emotional interaction decision making in human-computer interaction based on the concept of emotional cognitive evaluation 基于情感认知评价概念的人机交互情感交互决策研究

Proceedings of the 2022 3rd International Symposium on Big Data and Artificial Intelligence Pub Date : 2022-12-09 DOI: 10.1145/3598438.3598467

Ren-hua Yang, Jun Zhang

引用次数: 0

Research on Intelligent Scheduling of Foreign Flight Attendants' busy time Based on Parallel Genetic Algorithm 基于并行遗传算法的国外空乘繁忙时间智能调度研究

Proceedings of the 2022 3rd International Symposium on Big Data and Artificial Intelligence Pub Date : 2022-12-09 DOI: 10.1145/3598438.3598466

H. Ling

引用次数: 0

Study of optimal site selection for brand promotion based on simulated annealing and genetic algorithms 基于模拟退火和遗传算法的品牌推广最优选址研究

Proceedings of the 2022 3rd International Symposium on Big Data and Artificial Intelligence Pub Date : 2022-12-09 DOI: 10.1145/3598438.3598440

L. Tong

引用次数: 0

Research and Analysis of Post Information Matching and Data Mining Technology Based on BP Neural Network 基于BP神经网络的岗位信息匹配与数据挖掘技术研究与分析

Proceedings of the 2022 3rd International Symposium on Big Data and Artificial Intelligence Pub Date : 2022-12-09 DOI: 10.1145/3598438.3598459

F. Yuan

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Research on Digital Campus Construction Based on SOA Service Architecture 基于SOA服务架构的数字化校园建设研究

Proceedings of the 2022 3rd International Symposium on Big Data and Artificial Intelligence Pub Date : 2022-12-09 DOI: 10.1145/3598438.3598455

Li Jing, Otilia Manta

{"title":"Research on Digital Campus Construction Based on SOA Service Architecture","authors":"Li Jing, Otilia Manta","doi":"10.1145/3598438.3598455","DOIUrl":"https://doi.org/10.1145/3598438.3598455","url":null,"abstract":"The construction of educational informatization improves the comprehensive competitiveness, academic status and school-running level of colleges and universities. Information technology has also become the main driving force for colleges and universities to develop and change their school-running models, improve management efficiency and school-running levels, and create brands. At present, the software, hardware and implementation technologies used in information systems are not the same, and each application system is also maintained separately. These isolated application systems operate independently, cannot be interconnected, and have different data. There is no way to achieve data association, exchange and sharing. \"Information The problem of isolated islands has become increasingly prominent. This paper is based on Service-Oriented Architecture (Service-Oriented Architecture, SOA) from the perspective of business operations and processes, through the IT standard architecture and service modeling methods, integrating internal resources of universities, sharing existing resources between systems, Realize the construction goal of smart campus.","PeriodicalId":338722,"journal":{"name":"Proceedings of the 2022 3rd International Symposium on Big Data and Artificial Intelligence","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130153914","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Analysis of the Integration and Development of the Tea-tourism Industry based on Entropy Weight Method and Coupling Coordination Degree Model 基于熵权法和耦合协调度模型的茶旅游产业整合与发展分析

Proceedings of the 2022 3rd International Symposium on Big Data and Artificial Intelligence Pub Date : 2022-12-09 DOI: 10.1145/3598438.3598446

Y. Liu

引用次数: 0

Research and Analysis on the Evaluation of University Fusion System Based on Dynamic Group Strategy Teaching Optimization Algorithm 基于动态群体策略教学优化算法的高校融合系统评价研究与分析

Proceedings of the 2022 3rd International Symposium on Big Data and Artificial Intelligence Pub Date : 2022-12-09 DOI: 10.1145/3598438.3598464

Shang Xiaomei, Zeng Hui, Otilia Manta

引用次数: 0

Research on Chromatography Economic Analysis Method Based on MICCOR Algorithm 基于MICCOR算法的色谱经济分析方法研究

Proceedings of the 2022 3rd International Symposium on Big Data and Artificial Intelligence Pub Date : 2022-12-09 DOI: 10.1145/3598438.3598454

Lili Bao, Chen Du

{"title":"Research on Chromatography Economic Analysis Method Based on MICCOR Algorithm","authors":"Lili Bao, Chen Du","doi":"10.1145/3598438.3598454","DOIUrl":"https://doi.org/10.1145/3598438.3598454","url":null,"abstract":"As a separation and analysis technique, chromatography is widely used due to its high separation efficiency, fast speed, and high sensitivity. However, in practical applications, the characteristic variables are interrelated, and single, non-informational characteristic variables are interrelated are combined to represent the question under study. Therefore, this paper proposes a feature selection algorithm based on correlation features and maximum information coefficient (MICCOR). This algorithm uses a combination of linear correlation features to expand the information search space. These problems can be solved by selecting informative feature variables. at the same time, This paper analyzes the characteristics of big data and the methods and technical bottlenecks faced by statistics under the background. It expounds the relationship between chromatographic economic analysis and statistics and some functions that statistics needs to deal with big data due to its unique analytical functions and technical means. After further introducing the basic concept and theory of chromatographic economic analysis, taking consumer behavior analysis as an example to demonstrate the basic process of chromatographic economic analysis, and looking forward to the application prospect of chromatographic economic analysis as an innovative method of statistics in big data.","PeriodicalId":338722,"journal":{"name":"Proceedings of the 2022 3rd International Symposium on Big Data and Artificial Intelligence","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124573586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Effective Software Vulnerability Detection Method Based On Devised Deep-Learning Model To Fix The Vague Separation 一种基于设计的深度学习模型解决模糊分离的有效软件漏洞检测方法

Proceedings of the 2022 3rd International Symposium on Big Data and Artificial Intelligence Pub Date : 2022-12-09 DOI: 10.1145/3598438.3598452

Yuankun Liu, Yu Wang

{"title":"An Effective Software Vulnerability Detection Method Based On Devised Deep-Learning Model To Fix The Vague Separation","authors":"Yuankun Liu, Yu Wang","doi":"10.1145/3598438.3598452","DOIUrl":"https://doi.org/10.1145/3598438.3598452","url":null,"abstract":"SVD(Software Vulnerability Detection) methods based on automated deep learning is critical in software safety, they are designable and promising. Several function-level deep-learning SVD methods achieve an accuracy of up to 0.97 on open-source C/C++ datasets. However, as vulnerable samples have a low proportion in existing open-source datasets, these methods suffer from high false negative rate, they fail to identify cross-domain software vulnerabilities for neglecting the imbalance and vague separation of existing datasets. This paper proposes a novel framework based on the SeqGAN and TextCNN to fix the vague separation of aggregated 7 open-source C/C++ datasets, therefore improving the performance of SVD. As a result, SeqGAN&TextCNN scores 0.9385 of F1 score, compared with merely adopting the TextCNN, the method achieves an increase of 119% in recall and 31.31% in precision, and from the separations plotted by t-SNE, SeqGAN effectively improves the separation of original datasets. SeqGAN&TextCNN detects more vulnerable samples with low false negative rate, the method’ s F1 score is 79.58% higher than that of leveraging the VulDeePecker on 7 open-source C/C++ datasets.","PeriodicalId":338722,"journal":{"name":"Proceedings of the 2022 3rd International Symposium on Big Data and Artificial Intelligence","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121646031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0