Objective To discover the case-mix approach for TCM treatment of dominant disease type 2 diabetes patients and to analyze the hospitalization expense standards for different combinations of patients to provide theoretical references for better participation of TCM hospitals in the DRG payment method as well as reasonable regulation of hospitalization expenses for TCM type 2 diabetes patients in the future. Methods Case data were collected from 1,171 patients discharged with a principal diagnosis of type 2 diabetes from September 2021 to April 2023 from a tertiary care Chinese medicine hospital in Tianjin. Univariate and multivariate stepwise regression analyses determined categorical node variables. The decision tree model was used to perform case combinations and to analyze the expense standards and weights of different groups of disease types. Results The number of days of hospitalization, conditions in admission, and whether complicated cardiovascular and cerebrovascular diseases are the main factors affecting the hospitalization expense of type 2 diabetes patients in Chinese medicine hospitals, and the decision tree model was used to group the patients to form nine groups of patient case combinations. The standard of hospitalization expense for each combination was set reasonably. Conclusion The grouping results are more satisfactory, and the grouping scheme and hospitalization expense standards can provide a scientific basis for DRG grouping, adopting differentiated expense management, and improving the medical resource efficiency in TCM hospitals.
{"title":"A Decision Tree Model-based Study on the Grouping of Hospitalization Expenses of Type 2 Diabetes Patients in a Traditional Chinese Medicine Hospital","authors":"Xue Zhang, Jianke Ren, Xin Wang, Lijun Liang","doi":"10.62051/7d9h3y73","DOIUrl":"https://doi.org/10.62051/7d9h3y73","url":null,"abstract":"Objective To discover the case-mix approach for TCM treatment of dominant disease type 2 diabetes patients and to analyze the hospitalization expense standards for different combinations of patients to provide theoretical references for better participation of TCM hospitals in the DRG payment method as well as reasonable regulation of hospitalization expenses for TCM type 2 diabetes patients in the future. Methods Case data were collected from 1,171 patients discharged with a principal diagnosis of type 2 diabetes from September 2021 to April 2023 from a tertiary care Chinese medicine hospital in Tianjin. Univariate and multivariate stepwise regression analyses determined categorical node variables. The decision tree model was used to perform case combinations and to analyze the expense standards and weights of different groups of disease types. Results The number of days of hospitalization, conditions in admission, and whether complicated cardiovascular and cerebrovascular diseases are the main factors affecting the hospitalization expense of type 2 diabetes patients in Chinese medicine hospitals, and the decision tree model was used to group the patients to form nine groups of patient case combinations. The standard of hospitalization expense for each combination was set reasonably. Conclusion The grouping results are more satisfactory, and the grouping scheme and hospitalization expense standards can provide a scientific basis for DRG grouping, adopting differentiated expense management, and improving the medical resource efficiency in TCM hospitals.","PeriodicalId":509968,"journal":{"name":"Transactions on Computer Science and Intelligent Systems Research","volume":"14 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139167641","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}
Dunhuang Murals are one of China's intangible cultural heritages, which have received extensive attention. Identifying and classifying the dynasties of ancient murals quickly and accurately is extremely important for the study of Dunhuang Murals and the digital protection and inheritance. A method to classify Dunhuang Murals dynasties based on convolutional neural network (CNN) is proposed in this paper. First, the Dunhuang Murals data set is constructed from the mural materials; then, four convolutional neural network models with different depths and structures are constructed and trained; finally, the network model is tested using the test set and an appropriate classification model is selected. The experimental results show that for the Dunhuang mural image data sets of five different dynasties in this paper,the four models obtain high classification accuracy, and the accuracy of VGG11 and VGG19 reach 96%. Among them,the classification accuracy of murals in the Sui Dynasty and the Five Dynasties and Song Dynasties is lower than that of other dynasties in this paper.
{"title":"Research on Dynasty Classification of Dunhuang Murals Based on Convolutional Neural Networks","authors":"Yingdi Wan","doi":"10.62051/t1svva22","DOIUrl":"https://doi.org/10.62051/t1svva22","url":null,"abstract":"Dunhuang Murals are one of China's intangible cultural heritages, which have received extensive attention. Identifying and classifying the dynasties of ancient murals quickly and accurately is extremely important for the study of Dunhuang Murals and the digital protection and inheritance. A method to classify Dunhuang Murals dynasties based on convolutional neural network (CNN) is proposed in this paper. First, the Dunhuang Murals data set is constructed from the mural materials; then, four convolutional neural network models with different depths and structures are constructed and trained; finally, the network model is tested using the test set and an appropriate classification model is selected. The experimental results show that for the Dunhuang mural image data sets of five different dynasties in this paper,the four models obtain high classification accuracy, and the accuracy of VGG11 and VGG19 reach 96%. Among them,the classification accuracy of murals in the Sui Dynasty and the Five Dynasties and Song Dynasties is lower than that of other dynasties in this paper.","PeriodicalId":509968,"journal":{"name":"Transactions on Computer Science and Intelligent Systems Research","volume":"42 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139166895","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}
Artificial intelligence (AI) plus self-driving cars are commonly addressed as one in the technological realm of technology. Simply said, one cannot discuss one without discussing the other. Whilst AI is being implemented at breakneck speed in a multitude of sectors, the manner in which it is applied in the automotive industry has become a sensitive issue. Automakers all around the world are employing artificial intelligence in practically every step of the production process. Examples of AI in action include robots fitting together the initial nuts and bolts of an automobile or autonomous vehicles that use machine learning & vision to safely navigate around traffic.
{"title":"Artificial Intelligence in Cars Powers an AI Revolution in the Auto Industry","authors":"Xiankun Hou","doi":"10.62051/zn6ecc72","DOIUrl":"https://doi.org/10.62051/zn6ecc72","url":null,"abstract":"Artificial intelligence (AI) plus self-driving cars are commonly addressed as one in the technological realm of technology. Simply said, one cannot discuss one without discussing the other. Whilst AI is being implemented at breakneck speed in a multitude of sectors, the manner in which it is applied in the automotive industry has become a sensitive issue. Automakers all around the world are employing artificial intelligence in practically every step of the production process. Examples of AI in action include robots fitting together the initial nuts and bolts of an automobile or autonomous vehicles that use machine learning & vision to safely navigate around traffic.","PeriodicalId":509968,"journal":{"name":"Transactions on Computer Science and Intelligent Systems Research","volume":"51 13","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139166497","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}
Today, with the strong return of traditional culture, the integration of the two will deeply affect the protection of traditional handicrafts and the field of cultural communication. The industrialized production mode has gradually replaced the labor-intensive production mode, and handicrafts have gradually faded out of the public consumption field. The brain drain is serious, and many handicrafts with a long history have no successors. Under the background of AI(artificial intelligence) empowerment, this paper combines AI with traditional handicraft skills, and makes an in-depth study on the inheritance and dissemination of traditional handicraft skills. On this basis, it further thinks about the relationship between traditional handicraft skills display and experience, and the relationship between technology and experience, and studies the change of design concept from technology-oriented to human experience-oriented in traditional handicraft skills display design, and explores the development trend of experience design concept in future traditional handicraft skills display design. Develop the path and method of innovation, protection and inheritance with the comprehensive digital virtual traditional handicraft skill framework. The integration of AI and traditional culture will inevitably broaden and upgrade the path of inheritance and innovation of traditional handicraft skills, and make it achieve new development.
{"title":"Inheritance and Innovation of Traditional Handicraft Skills based on Artificial Intelligence","authors":"Yaping Zhang, Dongdong He","doi":"10.62051/rc69jc38","DOIUrl":"https://doi.org/10.62051/rc69jc38","url":null,"abstract":"Today, with the strong return of traditional culture, the integration of the two will deeply affect the protection of traditional handicrafts and the field of cultural communication. The industrialized production mode has gradually replaced the labor-intensive production mode, and handicrafts have gradually faded out of the public consumption field. The brain drain is serious, and many handicrafts with a long history have no successors. Under the background of AI(artificial intelligence) empowerment, this paper combines AI with traditional handicraft skills, and makes an in-depth study on the inheritance and dissemination of traditional handicraft skills. On this basis, it further thinks about the relationship between traditional handicraft skills display and experience, and the relationship between technology and experience, and studies the change of design concept from technology-oriented to human experience-oriented in traditional handicraft skills display design, and explores the development trend of experience design concept in future traditional handicraft skills display design. Develop the path and method of innovation, protection and inheritance with the comprehensive digital virtual traditional handicraft skill framework. The integration of AI and traditional culture will inevitably broaden and upgrade the path of inheritance and innovation of traditional handicraft skills, and make it achieve new development.","PeriodicalId":509968,"journal":{"name":"Transactions on Computer Science and Intelligent Systems Research","volume":"8 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139167875","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}
This paper aims to investigate a fractional order prey predator model with group defense and time delay through differential equation linearization theory and predictor-corrector scheme. In this model, we use the Holling-IV functional response, called Monod-Haldane function, for interactions between prey and predator species. Firstly, the uniqueness of the solution to the initial value problem of this system are proved. Secondly, the existence of equilibrium points is discussed, and the Hopf bifurcation of this system is studied using time lag as the bifurcation parameter. Finally, based on the predictor-corrector scheme, we conduct numerical simulations with corresponding parameters and different time delay parameters to analyze the impact of time delay on dynamics.
{"title":"Simulating the Influence of Time Delay on Fractional Differential Equations based on Predictor-Corrector Scheme","authors":"Cathy Tu","doi":"10.62051/h8w23956","DOIUrl":"https://doi.org/10.62051/h8w23956","url":null,"abstract":"This paper aims to investigate a fractional order prey predator model with group defense and time delay through differential equation linearization theory and predictor-corrector scheme. In this model, we use the Holling-IV functional response, called Monod-Haldane function, for interactions between prey and predator species. Firstly, the uniqueness of the solution to the initial value problem of this system are proved. Secondly, the existence of equilibrium points is discussed, and the Hopf bifurcation of this system is studied using time lag as the bifurcation parameter. Finally, based on the predictor-corrector scheme, we conduct numerical simulations with corresponding parameters and different time delay parameters to analyze the impact of time delay on dynamics.","PeriodicalId":509968,"journal":{"name":"Transactions on Computer Science and Intelligent Systems Research","volume":"40 17","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139166813","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}
This paper analyzes the historical sales data of vegetable products in a fresh food supermarket, and explores the automatic pricing and replenishment decision-making scheme of vegetable products in this supermarket. Firstly, we integrate and clean the attached data, and then we solve the characteristics and interrelationships of individual products and categories by establishing SARIMA model and Spearman's correlation coefficient model, and then we use nonlinear regression model, nonlinear autoregressive neural network model and optimization model to realize automatic pricing and replenishment decision-making for vegetable products.
{"title":"Automated Pricing and Replenishment Decision Modeling for Supermarket Vegetables","authors":"Luoyi Zheng, Zhiyan Lou","doi":"10.62051/t6g4w875","DOIUrl":"https://doi.org/10.62051/t6g4w875","url":null,"abstract":"This paper analyzes the historical sales data of vegetable products in a fresh food supermarket, and explores the automatic pricing and replenishment decision-making scheme of vegetable products in this supermarket. Firstly, we integrate and clean the attached data, and then we solve the characteristics and interrelationships of individual products and categories by establishing SARIMA model and Spearman's correlation coefficient model, and then we use nonlinear regression model, nonlinear autoregressive neural network model and optimization model to realize automatic pricing and replenishment decision-making for vegetable products.","PeriodicalId":509968,"journal":{"name":"Transactions on Computer Science and Intelligent Systems Research","volume":"11 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139167092","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}
The footwear landscape is evolving. Individuals seek a personalized shoe and insole fit for enhanced comfort and health. Historically, footwear sizes were measured manually. This traditional method faced challenges in scalability and precision. The study leveraged big data and machine learning to refine shoe size recommendations. Data was sourced from online platforms, foot scanning devices, and user feedback. Rigorous preprocessing ensured the data's consistency and normalization. Multiple machine learning models were evaluated, with the Random Forest algorithm emerging as the most effective. The findings highlighted an improvement in recommendation accuracy.The research indicates that the integration of technology and data holds the potential to transform the footwear industry, prioritizing comfort and health.
{"title":"Revolutionizing Footwear Recommendations: A Data-Driven Approach Harnessing Advanced Machine Learning Techniques","authors":"Sing Hoi Leo Zhuang","doi":"10.62051/66n15g82","DOIUrl":"https://doi.org/10.62051/66n15g82","url":null,"abstract":"The footwear landscape is evolving. Individuals seek a personalized shoe and insole fit for enhanced comfort and health. Historically, footwear sizes were measured manually. This traditional method faced challenges in scalability and precision. The study leveraged big data and machine learning to refine shoe size recommendations. Data was sourced from online platforms, foot scanning devices, and user feedback. Rigorous preprocessing ensured the data's consistency and normalization. Multiple machine learning models were evaluated, with the Random Forest algorithm emerging as the most effective. The findings highlighted an improvement in recommendation accuracy.The research indicates that the integration of technology and data holds the potential to transform the footwear industry, prioritizing comfort and health.","PeriodicalId":509968,"journal":{"name":"Transactions on Computer Science and Intelligent Systems Research","volume":"24 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139167349","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}
In recent years, deep learning models have greatly improved the performance of pedestrian detection and tracking. Although the accuracy of neural network-based modeling methods is high, they often require large computational and storage resource overheads, which makes them difficult to apply to robots with high resource requirements. Pedestrian tracking for robots still faces great challenges in the problems of occlusion, multi-target, and target loss. In this thesis, we focus on solving the problem of real-time pedestrian tracking by lightweight fusion of deep learning target detection models for robots, firstly, through the lightweight YOLO network, we perform pedestrian detection and feature extraction, and then we propose a Gaussian mixture model based feature matching method to construct the target pedestrian tracker, and finally, we use the PID-based control algorithm for real-time control of the robot's motion, and finally realize the real-time pedestrian Tracking. In this thesis, we validate the feature matching method based on the Gaussian mixture model on the ETH dataset, and at the same time, combined with the motion control algorithm, we carry out the actual validation, and the experimental results show that our proposed method can realize the real-time pedestrian tracking.
近年来，深度学习模型大大提高了行人检测和跟踪的性能。基于神经网络的建模方法虽然精度高，但往往需要大量的计算和存储资源开销，因此很难应用于对资源要求较高的机器人。机器人的行人跟踪仍然面临着遮挡、多目标和目标丢失等问题的巨大挑战。在本论文中，我们重点通过轻量级融合机器人深度学习目标检测模型来解决行人实时跟踪问题，首先通过轻量级YOLO网络进行行人检测和特征提取，然后提出基于高斯混合模型的特征匹配方法构建目标行人跟踪器，最后利用基于PID的控制算法对机器人的运动进行实时控制，最终实现行人实时跟踪。在本论文中，我们在 ETH 数据集上验证了基于高斯混合模型的特征匹配方法，同时结合运动控制算法进行了实际验证，实验结果表明我们提出的方法可以实现行人的实时跟踪。
{"title":"Robot Real-time Pedestrian Tracking Algorithm based on Deep Learning","authors":"Ziheng Qu","doi":"10.62051/vw8a4124","DOIUrl":"https://doi.org/10.62051/vw8a4124","url":null,"abstract":"In recent years, deep learning models have greatly improved the performance of pedestrian detection and tracking. Although the accuracy of neural network-based modeling methods is high, they often require large computational and storage resource overheads, which makes them difficult to apply to robots with high resource requirements. Pedestrian tracking for robots still faces great challenges in the problems of occlusion, multi-target, and target loss. In this thesis, we focus on solving the problem of real-time pedestrian tracking by lightweight fusion of deep learning target detection models for robots, firstly, through the lightweight YOLO network, we perform pedestrian detection and feature extraction, and then we propose a Gaussian mixture model based feature matching method to construct the target pedestrian tracker, and finally, we use the PID-based control algorithm for real-time control of the robot's motion, and finally realize the real-time pedestrian Tracking. In this thesis, we validate the feature matching method based on the Gaussian mixture model on the ETH dataset, and at the same time, combined with the motion control algorithm, we carry out the actual validation, and the experimental results show that our proposed method can realize the real-time pedestrian tracking.","PeriodicalId":509968,"journal":{"name":"Transactions on Computer Science and Intelligent Systems Research","volume":"21 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139167610","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}
Passive Internet of Things (IoT) is an emerging IoT technology that enables communication and data exchange between items through various sensors and devices. Sensor nodes do not require built-in batteries or other energy supply devices, but instead use external signals for operation. Radio Frequency Identification (RFID) technology is a simple and low-cost solution for the passive Internet of Things, suitable for scenarios that require simple tracking and monitoring of items. The sensor devices in this technology can be used for a long time interregional operation reduces maintenance costs and improves work efficiency. Therefore, it is a promising technology that can bring tremendous changes to various industries. In recent years, this technology has been widely applied in many fields, including logistics and supply chain management, industrial automation, intelligent agriculture, and health monitoring. This article elaborates on the practical application of the latest passive RFID technology, providing reference for more application scenarios in the future.
无源物联网（IoT）是一种新兴的物联网技术，通过各种传感器和设备实现物品之间的通信和数据交换。传感器节点不需要内置电池或其他能源供应装置，而是利用外部信号进行操作。射频识别（RFID）技术是一种简单、低成本的无源物联网解决方案，适用于需要对物品进行简单跟踪和监控的场景。该技术中的传感器设备可长期跨区域使用，降低了维护成本，提高了工作效率。因此，这是一项前景广阔的技术，能为各行各业带来巨大的变革。近年来，该技术已广泛应用于物流与供应链管理、工业自动化、智能农业、健康监测等多个领域。本文阐述了最新无源 RFID 技术的实际应用，为未来更多的应用场景提供参考。
{"title":"Application of Passive RFID Technology","authors":"Ziqing Li, Guiliang Feng","doi":"10.62051/jj9h9048","DOIUrl":"https://doi.org/10.62051/jj9h9048","url":null,"abstract":"Passive Internet of Things (IoT) is an emerging IoT technology that enables communication and data exchange between items through various sensors and devices. Sensor nodes do not require built-in batteries or other energy supply devices, but instead use external signals for operation. Radio Frequency Identification (RFID) technology is a simple and low-cost solution for the passive Internet of Things, suitable for scenarios that require simple tracking and monitoring of items. The sensor devices in this technology can be used for a long time interregional operation reduces maintenance costs and improves work efficiency. Therefore, it is a promising technology that can bring tremendous changes to various industries. In recent years, this technology has been widely applied in many fields, including logistics and supply chain management, industrial automation, intelligent agriculture, and health monitoring. This article elaborates on the practical application of the latest passive RFID technology, providing reference for more application scenarios in the future.","PeriodicalId":509968,"journal":{"name":"Transactions on Computer Science and Intelligent Systems Research","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139166623","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}
Focusing on computational linguistic approaches to English linguistics, this research explores how computational methods can be applied to dissect, understand and utilise the English language. We first looked at text analysis and processing, delving into natural language processing techniques such as text categorisation, sentiment analysis and machine translation, and their application to social media and automated text processing. In the area of lexicography and semantics, we explored how techniques such as distributed word vectors, semantic role labelling and sentiment analysis can deepen our understanding of vocabulary and semantics. We highlight the importance of these techniques in natural language processing tasks such as sentiment analysis and information retrieval. In addition, we focus on cross-language comparative and multilingual research, emphasising how big data and cross-language comparative research can reveal similarities and differences between languages and their implications for global linguistics. Finally, we explore corpus linguistics and big data analytics, highlighting the richness of linguistic data and tools they provide for linguistic research. Overall, this study highlights the importance of computational linguistic approaches to English linguistics and how they have transformed the way linguistics is studied and language technology has evolved. Future research trends will continue to drive the further development of computational linguistics methods, leading to a closer integration of linguistics with big data analytics and computational methods, creating more opportunities for the future of the field of linguistics.
{"title":"A Computational Linguistic Approach to English Lexicography","authors":"Fan Yang","doi":"10.62051/wepk6t89","DOIUrl":"https://doi.org/10.62051/wepk6t89","url":null,"abstract":"Focusing on computational linguistic approaches to English linguistics, this research explores how computational methods can be applied to dissect, understand and utilise the English language. We first looked at text analysis and processing, delving into natural language processing techniques such as text categorisation, sentiment analysis and machine translation, and their application to social media and automated text processing. In the area of lexicography and semantics, we explored how techniques such as distributed word vectors, semantic role labelling and sentiment analysis can deepen our understanding of vocabulary and semantics. We highlight the importance of these techniques in natural language processing tasks such as sentiment analysis and information retrieval. In addition, we focus on cross-language comparative and multilingual research, emphasising how big data and cross-language comparative research can reveal similarities and differences between languages and their implications for global linguistics. Finally, we explore corpus linguistics and big data analytics, highlighting the richness of linguistic data and tools they provide for linguistic research. Overall, this study highlights the importance of computational linguistic approaches to English linguistics and how they have transformed the way linguistics is studied and language technology has evolved. Future research trends will continue to drive the further development of computational linguistics methods, leading to a closer integration of linguistics with big data analytics and computational methods, creating more opportunities for the future of the field of linguistics.","PeriodicalId":509968,"journal":{"name":"Transactions on Computer Science and Intelligent Systems Research","volume":"19 15","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139167442","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}
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