Pub Date : 2023-01-06DOI: 10.1109/ICCECE58074.2023.10135442
Kangyong Yin, Haosheng Huang, Hongwu Xiao, Wei Liang, Zhongwei Sun, Lei Wang
Sharing content, such as video, with others via personal mobile devices has become more and more popular. However, it tends to incur extremely high traffic fee to share large files in commercial networks. In this paper, we propose an efficient network-coding-based content sharing scheme (NCCSS) for mobile devices via WiFi Direct. When the file owner wants to share a file to others, it equally splits the file into multiple pieces, and then linearly encodes the pieces into segments with random linear network coding (RLNC). After that, it switches itself to an access point (AP), and waits to accept request from other devices. For each device in the network, it connects to the AP, and requests linearly independent segments. After it has received a fixed number of encoded segments, it switches itself to a new AP to enlarge the coverage of sharing. By strategically switching devices between the AP mode and ordinary mode, all devices could receive sufficient segments and recover the original file. NCCSS was evaluated in a real-world testbed consisting of 20 mobile devices. The experimental results show that compared to the traditional replication-based transmission scheme and erasure-coding-based transmission scheme, NCCSS could provide higher sharing rate.
{"title":"Network-Coding-Based Content Sharing for Mobile Devices via Multiple Relays of WiFi Direct","authors":"Kangyong Yin, Haosheng Huang, Hongwu Xiao, Wei Liang, Zhongwei Sun, Lei Wang","doi":"10.1109/ICCECE58074.2023.10135442","DOIUrl":"https://doi.org/10.1109/ICCECE58074.2023.10135442","url":null,"abstract":"Sharing content, such as video, with others via personal mobile devices has become more and more popular. However, it tends to incur extremely high traffic fee to share large files in commercial networks. In this paper, we propose an efficient network-coding-based content sharing scheme (NCCSS) for mobile devices via WiFi Direct. When the file owner wants to share a file to others, it equally splits the file into multiple pieces, and then linearly encodes the pieces into segments with random linear network coding (RLNC). After that, it switches itself to an access point (AP), and waits to accept request from other devices. For each device in the network, it connects to the AP, and requests linearly independent segments. After it has received a fixed number of encoded segments, it switches itself to a new AP to enlarge the coverage of sharing. By strategically switching devices between the AP mode and ordinary mode, all devices could receive sufficient segments and recover the original file. NCCSS was evaluated in a real-world testbed consisting of 20 mobile devices. The experimental results show that compared to the traditional replication-based transmission scheme and erasure-coding-based transmission scheme, NCCSS could provide higher sharing rate.","PeriodicalId":120030,"journal":{"name":"2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122823002","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}
Pub Date : 2023-01-06DOI: 10.1109/ICCECE58074.2023.10135197
Zhili Liu, Heyang Sun, Jinliang Song, Bin Zhang, Yuhang Yan, Bingbing Qiu, Lihang Jiang, Jingjing Li
With the development of the electric power system, the construction of electric power credit has achieved positive results, but there is still a certain gap compared with the requirements of the government and enterprises. In this paper, a vertical federated learning framework including user credit evaluation is proposed. By constructing a vertical federated learning credit sharing system between electric power companies and financial companies, the information barriers of both are reduced and the market transaction risks are reduced. Through the construction of refined electricity price pricing model based on user credit evaluation, it is beneficial to reduce the cost and increase the efficiency of users, and encourage users to develop with high credit and high quality.
{"title":"Vertical Federated Learning Architecture for Power Company and Financial Company and Electricity Pricing Model Considering User Credit Evaluation","authors":"Zhili Liu, Heyang Sun, Jinliang Song, Bin Zhang, Yuhang Yan, Bingbing Qiu, Lihang Jiang, Jingjing Li","doi":"10.1109/ICCECE58074.2023.10135197","DOIUrl":"https://doi.org/10.1109/ICCECE58074.2023.10135197","url":null,"abstract":"With the development of the electric power system, the construction of electric power credit has achieved positive results, but there is still a certain gap compared with the requirements of the government and enterprises. In this paper, a vertical federated learning framework including user credit evaluation is proposed. By constructing a vertical federated learning credit sharing system between electric power companies and financial companies, the information barriers of both are reduced and the market transaction risks are reduced. Through the construction of refined electricity price pricing model based on user credit evaluation, it is beneficial to reduce the cost and increase the efficiency of users, and encourage users to develop with high credit and high quality.","PeriodicalId":120030,"journal":{"name":"2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131559186","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}
Pub Date : 2023-01-06DOI: 10.1109/ICCECE58074.2023.10135281
Jiabin Zhang, Xiaoru Wang, Han Xia, Xiaolong Li
Recently, several computer vision tasks have begun to adopt transformer-based approaches with promising results. Using a completely transformer-based architecture in image recovery achieves better performance than the existing CNN approach, but the existing vision transformers lack the scalability for high-resolution images, which means that transformers are underutilized in image restoration tasks. We propose a hybrid architecture (HCT) that uses both CNN and transformer to improve image restoration. HCT consists of transformer and CNN branches. By fully integrating the two branches, we strengthen the network's ability of parameter sharing and local information aggregation, and also increase the network's ability to integrate global information, and finally achieve the purpose of improving the image recovery effect. Our proposed transformer branch uses a spatial fusion adaptive attention model that blends local and global attention improving image restoration while reducing computing costs. Extensive experiments show that HCT achieves competitive results in super-resolution tasks.
{"title":"HCT: Hybrid CNN-Transformer Networks for Super-Resolution","authors":"Jiabin Zhang, Xiaoru Wang, Han Xia, Xiaolong Li","doi":"10.1109/ICCECE58074.2023.10135281","DOIUrl":"https://doi.org/10.1109/ICCECE58074.2023.10135281","url":null,"abstract":"Recently, several computer vision tasks have begun to adopt transformer-based approaches with promising results. Using a completely transformer-based architecture in image recovery achieves better performance than the existing CNN approach, but the existing vision transformers lack the scalability for high-resolution images, which means that transformers are underutilized in image restoration tasks. We propose a hybrid architecture (HCT) that uses both CNN and transformer to improve image restoration. HCT consists of transformer and CNN branches. By fully integrating the two branches, we strengthen the network's ability of parameter sharing and local information aggregation, and also increase the network's ability to integrate global information, and finally achieve the purpose of improving the image recovery effect. Our proposed transformer branch uses a spatial fusion adaptive attention model that blends local and global attention improving image restoration while reducing computing costs. Extensive experiments show that HCT achieves competitive results in super-resolution tasks.","PeriodicalId":120030,"journal":{"name":"2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127696149","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}
Pub Date : 2023-01-06DOI: 10.1109/ICCECE58074.2023.10135325
Weijuan Li, R. Jia
We present SA-MVSNet, a novel two-stage multi-view stereo network equipped with self-attention mechanism, which can improve the quality of low-resolution image 3D reconstruction. SA-MVSNet consists of two stages, and the lower resolution depth maps predicted in the first stage provide a priori information for the second stage. To increase the utilization of image information, a pyramid scheme was used to fuse the feature maps at different resolutions. Moreover, we introduce an improved self-attention module in the first stage to improve reconstruction accuracy by learning the long-term dependence information of feature maps. The experiments on the DTU dataset show a promising result in both completeness and accuracy metrics of the 3D scene reconstructed by the proposed method.
{"title":"A Self-Attention based Network for Low Resolution Multi-View Stereo","authors":"Weijuan Li, R. Jia","doi":"10.1109/ICCECE58074.2023.10135325","DOIUrl":"https://doi.org/10.1109/ICCECE58074.2023.10135325","url":null,"abstract":"We present SA-MVSNet, a novel two-stage multi-view stereo network equipped with self-attention mechanism, which can improve the quality of low-resolution image 3D reconstruction. SA-MVSNet consists of two stages, and the lower resolution depth maps predicted in the first stage provide a priori information for the second stage. To increase the utilization of image information, a pyramid scheme was used to fuse the feature maps at different resolutions. Moreover, we introduce an improved self-attention module in the first stage to improve reconstruction accuracy by learning the long-term dependence information of feature maps. The experiments on the DTU dataset show a promising result in both completeness and accuracy metrics of the 3D scene reconstructed by the proposed method.","PeriodicalId":120030,"journal":{"name":"2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132629244","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}
Pub Date : 2023-01-06DOI: 10.1109/ICCECE58074.2023.10135369
Heng Zhang, Lishan Jia
ATC training simulation system is widely used in controller training. The track display module is an important part of ATC training simulation system. The low-cost simulation system based on microcomputer has the characteristics of low cost and high simulation degree. This paper is based on the modeling method of improved Euler angle formula, and then improves the longitude and latitude update algorithm. Finally, the GL Studio graphic designer updates the control interface design according to the standard instrument approach diagram of Capital Airport, and uses the virtual pilot model to realize the simulation of the track display module in the aircraft approach phase through the VC++software compilation platform. The practice proves that the design method makes the simulation system interface clear and the aircraft target motion real-time.
{"title":"Construction of Aircraft Approach Simulation System based on Virtual Pilot Model","authors":"Heng Zhang, Lishan Jia","doi":"10.1109/ICCECE58074.2023.10135369","DOIUrl":"https://doi.org/10.1109/ICCECE58074.2023.10135369","url":null,"abstract":"ATC training simulation system is widely used in controller training. The track display module is an important part of ATC training simulation system. The low-cost simulation system based on microcomputer has the characteristics of low cost and high simulation degree. This paper is based on the modeling method of improved Euler angle formula, and then improves the longitude and latitude update algorithm. Finally, the GL Studio graphic designer updates the control interface design according to the standard instrument approach diagram of Capital Airport, and uses the virtual pilot model to realize the simulation of the track display module in the aircraft approach phase through the VC++software compilation platform. The practice proves that the design method makes the simulation system interface clear and the aircraft target motion real-time.","PeriodicalId":120030,"journal":{"name":"2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132240409","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}
Pub Date : 2023-01-06DOI: 10.1109/ICCECE58074.2023.10135538
Sicong Chen, Chaobing Huang
The use of remote sensing images for ship detection can accurately monitor ship targets and provide reliable reference for monitoring key sea areas. Since the horizontal detection model cannot precisely locate and represent the specific direction of the ship, we propose a rotation detector based on YOLOv5m6 and KFIoU, which can realize the detection of ships in arbitrary orientations. On the other hand, the punishment based on Gaussian Wasserstein distance is used in model to generate confidence loss, which improves the discrimination between foreground and background during ship detection. Finally, transformer pyramid attention is added to the backbone of network, which uses the fusion of information extracted in multi-scale space and the self-attention mechanism to improve the feature extraction effect and the accuracy of detection. On FGSD2021 dataset, our model finally achieves 88.24% of mAP after adding attention mechanism and improving the confidence loss.
{"title":"RDYOLOv5m6-KF: A Rotation Detector for Ship Detection in Remote Sensing Images","authors":"Sicong Chen, Chaobing Huang","doi":"10.1109/ICCECE58074.2023.10135538","DOIUrl":"https://doi.org/10.1109/ICCECE58074.2023.10135538","url":null,"abstract":"The use of remote sensing images for ship detection can accurately monitor ship targets and provide reliable reference for monitoring key sea areas. Since the horizontal detection model cannot precisely locate and represent the specific direction of the ship, we propose a rotation detector based on YOLOv5m6 and KFIoU, which can realize the detection of ships in arbitrary orientations. On the other hand, the punishment based on Gaussian Wasserstein distance is used in model to generate confidence loss, which improves the discrimination between foreground and background during ship detection. Finally, transformer pyramid attention is added to the backbone of network, which uses the fusion of information extracted in multi-scale space and the self-attention mechanism to improve the feature extraction effect and the accuracy of detection. On FGSD2021 dataset, our model finally achieves 88.24% of mAP after adding attention mechanism and improving the confidence loss.","PeriodicalId":120030,"journal":{"name":"2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134155305","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 normal operation of power transformer is related to the safety and stability of the power grid. Abnormal temperature may cause damage to transformer equipment, seriously affect its service life, and even lead to major accidents. In this paper, a transformer temperature prediction method based on big data is proposed. The ambient temperature is included in the prediction conditions. A feature extraction method based on adaptive weighting is designed to mine the time series features in the column head temperature and ambient temperature, and an interactive feature fusion strategy is used to form a comprehensive and reliable transformer temperature prediction. The experimental simulation shows that the transformer temperature prediction method proposed in this paper has high prediction accuracy, effectively provides more quantitative auxiliary information for the operation monitoring of power transformer equipment, ensures the safe and stable operation of transformer, and has high practicability.
{"title":"Big Data Analysis Based Transformer Temperature Prediction Method in Distribution Station Area","authors":"Xianming Cheng, Haipeng Sun, Zhibin Yin, Xiao Ding","doi":"10.1109/ICCECE58074.2023.10135457","DOIUrl":"https://doi.org/10.1109/ICCECE58074.2023.10135457","url":null,"abstract":"The normal operation of power transformer is related to the safety and stability of the power grid. Abnormal temperature may cause damage to transformer equipment, seriously affect its service life, and even lead to major accidents. In this paper, a transformer temperature prediction method based on big data is proposed. The ambient temperature is included in the prediction conditions. A feature extraction method based on adaptive weighting is designed to mine the time series features in the column head temperature and ambient temperature, and an interactive feature fusion strategy is used to form a comprehensive and reliable transformer temperature prediction. The experimental simulation shows that the transformer temperature prediction method proposed in this paper has high prediction accuracy, effectively provides more quantitative auxiliary information for the operation monitoring of power transformer equipment, ensures the safe and stable operation of transformer, and has high practicability.","PeriodicalId":120030,"journal":{"name":"2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124761408","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}
With the rise of computer vision, it is becoming more and more important to accurately recognize and evaluate human actions. However, the complexity, intraclass differences, and viewing angle changes of human actions significantly impact the accuracy of identification human actions. This paper proposed an action recognition and evaluation method based on skeleton information extraction. Briefly, We use Lightweight OpenPose to extract the key points of human skeleton and perform processing work, including video data cutting, deleting some key points, supplementing missing key points, filtering processing, feature extraction, etc. Through an in-depth exploration of related theoretical technologies, we proposed a model for recognition and evaluation of human table tennis actions with an ordinary camera. The support vector machine algorithm (SVM) classification model is used to identify table tennis actions in real-time. Then the dynamic time regularization (DTW) algorithm calculates the similarity of each human skeleton key point in the action sequence. The low-scoring bone key points are marked to evaluate the human table tennis action in real time. The results show that a recognition rate of more than 95% is achieved in the test set, which proves the method's effectiveness. In addition, we compared the results with previous work using inertial sensors for action recognition, which shows our method can preserve the same accuracy with a much lower cost of implementation.
{"title":"Human Table Tennis Actions Recognition and Evaluation Method Based on Skeleton Extraction","authors":"Wuzhe Huang, Jingjing Yang, Hongde Luo, Heng Zhang","doi":"10.1109/ICCECE58074.2023.10135318","DOIUrl":"https://doi.org/10.1109/ICCECE58074.2023.10135318","url":null,"abstract":"With the rise of computer vision, it is becoming more and more important to accurately recognize and evaluate human actions. However, the complexity, intraclass differences, and viewing angle changes of human actions significantly impact the accuracy of identification human actions. This paper proposed an action recognition and evaluation method based on skeleton information extraction. Briefly, We use Lightweight OpenPose to extract the key points of human skeleton and perform processing work, including video data cutting, deleting some key points, supplementing missing key points, filtering processing, feature extraction, etc. Through an in-depth exploration of related theoretical technologies, we proposed a model for recognition and evaluation of human table tennis actions with an ordinary camera. The support vector machine algorithm (SVM) classification model is used to identify table tennis actions in real-time. Then the dynamic time regularization (DTW) algorithm calculates the similarity of each human skeleton key point in the action sequence. The low-scoring bone key points are marked to evaluate the human table tennis action in real time. The results show that a recognition rate of more than 95% is achieved in the test set, which proves the method's effectiveness. In addition, we compared the results with previous work using inertial sensors for action recognition, which shows our method can preserve the same accuracy with a much lower cost of implementation.","PeriodicalId":120030,"journal":{"name":"2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132603050","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}
Pub Date : 2023-01-06DOI: 10.1109/ICCECE58074.2023.10135440
Shuai Wang, Tao Sun, Xiao Han Li, Hao Ran Kong, Chao Feng
RRT* algorithm has some shortcomings, such as slow convergence speed and long path length. To solve these problems, an improved algorithm based on RRT* is proposed. By optimizing the sampling part of RRT* algorithm, the algorithm guides the random tree to grow towards the target point, which greatly improves the planning speed. Then, a path optimization strategy is proposed to reduce the redundant inflection points in the path and reduce the cost of the path. Finally, the effectiveness of the algorithm is verified by simulation experiments.
{"title":"An Improved Path Planning Algorithm Based on RRT*","authors":"Shuai Wang, Tao Sun, Xiao Han Li, Hao Ran Kong, Chao Feng","doi":"10.1109/ICCECE58074.2023.10135440","DOIUrl":"https://doi.org/10.1109/ICCECE58074.2023.10135440","url":null,"abstract":"RRT* algorithm has some shortcomings, such as slow convergence speed and long path length. To solve these problems, an improved algorithm based on RRT* is proposed. By optimizing the sampling part of RRT* algorithm, the algorithm guides the random tree to grow towards the target point, which greatly improves the planning speed. Then, a path optimization strategy is proposed to reduce the redundant inflection points in the path and reduce the cost of the path. Finally, the effectiveness of the algorithm is verified by simulation experiments.","PeriodicalId":120030,"journal":{"name":"2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133998811","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}
Pub Date : 2023-01-06DOI: 10.1109/ICCECE58074.2023.10135210
Lulu Zhang, Junru Li, Dacheng Feng, Junjie Sun
The rise of the strategy of “Internet +” breaks the barriers of data and information. Web crawler is widely used in data acquisition and data analysis in the massive Internet plus information. Taking “IMDB top250 movies” as the goal, using the crawler technology based on Python language, this paper explains the four steps of web crawler in detail, compares the differences of three web page parsing methods: BeautifulSoup, Regular Expression(Re) and XPath, and completes the crawling of target data. The experimental results show that Re is the best in data analysis speed; In terms of web page parsing logic, beautiful soup is the best; From the perspective of comprehensive use, XPath is more suitable.
{"title":"Design And Implementation of Web Crawler Based on 'Internet +'Data Automatic Extraction","authors":"Lulu Zhang, Junru Li, Dacheng Feng, Junjie Sun","doi":"10.1109/ICCECE58074.2023.10135210","DOIUrl":"https://doi.org/10.1109/ICCECE58074.2023.10135210","url":null,"abstract":"The rise of the strategy of “Internet +” breaks the barriers of data and information. Web crawler is widely used in data acquisition and data analysis in the massive Internet plus information. Taking “IMDB top250 movies” as the goal, using the crawler technology based on Python language, this paper explains the four steps of web crawler in detail, compares the differences of three web page parsing methods: BeautifulSoup, Regular Expression(Re) and XPath, and completes the crawling of target data. The experimental results show that Re is the best in data analysis speed; In terms of web page parsing logic, beautiful soup is the best; From the perspective of comprehensive use, XPath is more suitable.","PeriodicalId":120030,"journal":{"name":"2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116506090","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：